Miracle-dz/UniFAR-FTUs huggingface dataset:
Cosmic-Ray Energy Spectrum' and, High-Energy Particles in Supernova 805

According to Syrovatsky, the cosmic-ray energy spectrum is obtained in the form of a power law by assuming an equipartition of source energy among the magnetic field, turbulence and high-energy particles in the cosmic-ray source. This mechanism is extended to the case where the volume of the source is changing with time. Some studies are made about a model which is suited to the mechanism: The energy distribution in the source is sharp for protons and broad for electrons. The sharp one is due to the fact that the injection in the accelerating region is dominant only in the initial stage at the supernova explosion. The secondary electrons from protons give rise to a luminosity maximum at the explosion by synchrotron mechanism.
Cheating and Chegg: A Retrospective

In the spring of 2020, universities across America, and the world, abruptly transitioned to online learning. The online transition required faculty to find novel ways to administer assessments and in some cases, for students to utilize novel ways of cheating in their classes. The purpose of this paper is to provide a retrospective on cheating during online exams in the spring of 2020. It specifically looks at honor code violations in a sophomore level engineering course that enrolled more than 200 students. In this particular course, four pre-COVID assessments were given in class and six mid-COVID assessments were given online. This paper examines the increasing rate of cheating on these assessments and the profiles of the students who were engaged in cheating. It compares students who were engaged in violations of the honor code by uploading exam questions vs. those who those who looked at solutions to uploaded questions. This paper also looks at the abuse of Chegg during exams and the responsiveness of Chegg's honor code team. It discusses the effectiveness of Chegg's user account data in pursuing academic integrity cases. Information is also provided on the question response times for Chegg tutors in answering exam questions and the actual efficacy of cheating in this fashion. © American Society for Engineering Education, 2021
Atmospheric Response to the Quasi-Resonant Growth of Forced Planetary Waves

The forcing of the second-order zonally-averaged wind and temperature fields due to the quasiresonant growth of planetary waves in a two-layer model is considered. Dissipation in the form of linear drag and Newtonian cooling is allowed for. Calculations are made in a mid-latitude * -plane channel bounded by two vertical walls . The linear or first order solution is constrained so as to not transport momentum meridionally. Three neutral modes in the adiabatic two layer model are brought to resonance separately by adjusting the basic zonal flow configuration. For a dissipation time scale of 2 days, the quasi-resonant enhancement of the response is negligible. A time scale of 4 days is used. For resonance involving the two layer equivalent of the Rossby wave, the strong westerly zonal flow configuration causes most of the second order effects to be confined to the lowest few scale heights, where a slow easterly acceleration of the zonal flow occurs. A second resonance associated with weak westerlies surmounted by moderate westerlies leads to a very rapid high level easterly acceleration lasting about two weeks. A final resonant wind configuration with easterlies above westerlies is associated with very rapid temperature rises near the pole. Calculations suggest that the quasi-resonant enhancement of the planetary wave-zone flow interaction resulting from certain basic flow configurations might be the explanation of the stratospheric warming. It is hypothesized that the timing of warmings is determined by how well tuned the zonal flow structure is in the sense that appreciable secondorder effects will result in response to small influxes of planetary-wave energy from below. Furthermore, it is suggested that the subsequent evolution of a warming into a full scale warming depends on the ability of the zonal flow configuration to evolve through a series of tuned or resonant states.
Advances in blind source separation for spatial data

Multivariate data where each measurement is taken at a different location in space are encountered in many practical applications. Typical features of such data are that measurements in close proximity tend to be more similar than the ones further separated. Proper statistical tools need to account for this fact. Recently, the popular blind source separation methodology was formulated for such spatial data denoted as spatial blind source separation (SBSS). Specifically, it is assumed that the observed data is formed by linear combinations of unobserved components. Recovering these latent components is very beneficial as they are uncorrelated, most often show underlying physical processes that generated the data and for domain experts it is highly likely that only a few components are of interest. All advantages were proven on a geochemical dataset. However, the original SBSS only considers the case when all components are of equal interest and are invariant under translation in space (second-order stationarity). This thesis extends these methods for various features commonly present in spatial data. Namely, first and second order non-stationarity or noisy spatial data. Furthermore, the usefulness of blind source separation in spatial regression as well as spatial prediction is investigated.
Validation of the Key Active Ingredients and Anti-In ﬂ ammatory and Analgesic Effects of Shenjin Huoxue Mixture Against Osteoarthritis by Integrating Network Pharmacology Approach and Thin-Layer Chromatography Analysis

Background: Shenjin Huoxue Mixture (SHM), a classic traditional herb mixture has shown signi ﬁ cant clinical ef ﬁ cacy against osteoarthritis (OA). Our previous experimental study has con ﬁ rmed its anti – in ﬂ ammatory and analgesic effect on acute soft tissue injury in rats, with the compound of glycyrrhizinate in SHM identi ﬁ ed and the content of paeoni ﬂ orin in SHM determined by high-performance liquid chromatography (HPLC). However, the components and its pharmacological mechanisms of SHM against OA have not been systematically elucidated yet. Thus this study aimed to predict the key active ingredients and potential pharmacological mechanisms of SHM in the treatment of OA by network pharmacology approach and thin-layer chromatography (TLC) validation. Methods: The active ingredients of SHM and their targets, as well as OA-related targets, were identi ﬁ ed from databases. The key active ingredients were de ﬁ ned and ranked by the number of articles retrieved in PubMed using the keyword “ (the active ingredients [Title/Abstract]) AND Osteoarthritis[Title/Abstract] ” , and validated partially by TLC. The pharmacological mechanisms of SHM against OA were displayed by GO term and Reactome pathway enrichment analysis with Discovery Studio 3.0 software docking to testing the reliability. Results: Finally, 16 key active ingredients were identi ﬁ ed and ranked, including quercetin validated through TLC. In ﬂ ammatory response, IL-6 signaling pathway and toll-like receptor (TLR) cascades pathway were predicted as the main pharmacological mechanisms of SHM against OA. Especially, 12 out of 16 key active ingredients, including validated quercetin, were well docked to IL-6 proteins. Conclusion: Our results con ﬁ rmed the anti – in ﬂ ammatory and analgesic effect of SHM against OA through multiple components, multiple targets and multiple pathways, which revealed the theoretical basis of SHM against OA and may provide a new drug option for treating OA.
A Comprehensive Workplace Environment based on a Deep Learning Architecture for Cognitive Systems

—Many technical work places, such as laboratories or test beds, are the setting for well-deﬁned processes requiring both high precision and extensive documentation, to ensure accuracy and support accountability that often is required by law, science, or both. In this type of scenario, it is desirable to delegate certain routine tasks, such as documentation or preparatory next steps, to some sort of automated assistant, in order to increase precision and reduce the required amount of manual labor in one fell swoop. At the same time, this automated assistant should be able to interact adequately with the human worker, to ensure that the human worker receives exactly the kind of support that is required in a certain context. To achieve this, we introduce a multilayer architecture for cognitive systems that structures the system’s computation and reasoning across well-deﬁned levels of abstraction, from mass signal processing up to organization-wide, intention-driven reasoning. By partitioning the architecture into well-deﬁned, distinct layers, we reduce complexity and thus facilitate both the implementation and the training of the cognitive system. Each layer comprises a building block that adheres to a speciﬁc structural pattern, consisting of storage, processing units and components that are used for training. We incorporate ensemble methods to allow for a modular expansion of a speciﬁc layer, thus making it possible to introduce pre-trained functional blocks into the system. In addition, we provide strategies for generating synthetical data that support the training of the neural network parts within the processing layers. On this basis, we outline the functional modules of a cognitive system supporting the execution of partially manual processes in technical work places. Finally, a prototypical implementation serves as a proof of concept for this multilayer architecture.
T HE E FFECT OF T RAINING AT A S PECIFIC T IME OF D AY : A R EVIEW

N. The effect of training at a speciﬁc time of day: A review. J Strength Cond Res 26(7): 1984–2005, 2012—This article focuses on physical performances after training at a speciﬁc time of day. To date, although the effect of time of day on aerobic performances
An Improved Convolutional Neural Network with LSTM Approach for Texture Classification

Texture classification is a problem that has several applications, such as remote detection and recognition of forest species. Solutions tend to be customized for the dataset used, but are not generalized. Machine learning algorithms play an important role in the current Texture Classification. However, these algorithms are suffering with low accuracy and classification rate. Deep learning is another sophisticated technique to solve these challenges because texture classification performance is not strong in traditional machine learning systems. The Convolutional Neural Network (CNN) in combination with Long Short-Term Memory (LSTM) forms a robust selection between a powerful invariant feature extractor and an accurate classifier. This model should automatically determine the efficient properties of the feature samples so that the texture samples can be classified accurately. Expert fusion provides stability in classification rates between different data sets and the proposed model will significantly increases texture classification performance. From the experimental analysis, it is ascertained that CNN-LSTM is outperforms with existing state of the art of the algorithms SVM and CNN.
Restoration of tiger ( Panthera tigris ) follicles from frozen-thawed ovarian tissues

Ovarian tissue cryopreservation has been proposed as a tool to conserve the valuable genetics of endangered species. However, sustaining the viability of follicles and oocytes enclosed within the frozen-thawed tissues is important for the application of this technology. This study evaluated the impact of eCG supplementation on the viability and growth of tiger follicles and oocytes within frozen-thawed ovarian tissues during in vitro culture. Six frozen-thawed ovarian fragments from a tiger obtained post-ovariohysterectomy were included. Twelve antral follicles were mechanically isolated from the ovarian fragments and randomly allocated to two culture conditions (control and 0.05 IU/mL eCG supplementation) and cultured in an alginate hydrogel for 3 days. Follicle growth was evaluated on Day 0 and 3 using Image J software. At the end of the culture, follicles were removed from the hydrogel and stained with neutral red to assess follicle viability. The oocytes were thereafter recovered and evaluated for nuclear status using Hoechst 33258 dye. Follicle diameter in the control group significantly decreased ( P < 0.05), whereas that of the eCG supplementation group increased their relative growth ( P < 0.05). The oocyte recovery rate from cultured follicles was 33% and 67% in the control and eCG groups respectively ( P > 0.05). All recovered oocytes remained in the germinal vesicle phase. The present study showed that tiger frozen-thawed antral follicles could maintain their viability and structure when eCG was supplemented in the culture medium. In conclusion, viable oocytes within follicles can be rescued from the tiger ovarian tissues post-mortem.
Comparative performances of indigenous, Vanaraja and crossbred (PB2xIndigenous) chicken under different systems of rearing

A study has been conducted on a total 1200 no. of chicks out of which 600 numbers (200 each of Indigenous, Vanaraja and Crossbred) were reared under intensive system. All the types of chicken were fed uniform diet of Chick (0-8 weeks), Grower (9-20 weeks) and Layer (above 20 weeks) rations. Remaining 600 numbers (200 each of Indigenous, Vanaraja and Crossbred) were distributed among 30 beneficiaries for backyard system of rearing. Significant ( P ≤0.05) differences in body weights were recorded among the different types of chicken at all the specified ages. The overall mean body weight was found to be significantly ( P≤ 0.05) higher in Vanaraja (2816.80 ± 26.05 g) followed by Crossbred (2333.70 ± 16.11 g) and Indigenous (1412.70 ± 12.61g) chickens at 52 weeks of age. Irrespective of types of chicken, significantly ( P ≤0.05) higher body weight was recorded under intensive system (2356.03 ± 30.02 g) than that of backyard system (2019.43 ± 27.65 g) of rearing. The average total feed consumption was significantly ( P ≤0.05) higher in Vanaraja than Crossbred and Indigenous chicken up to 20 and 52 weeks of age. The FCR was found to be better in Vanaraja (4.30 ± 0.12) followed by Crossbred (4.69 ± 0.15) and Indigenous (6.02± 0.40) chickens.
E-Cigarettes A Scientific Review

Electronic cigarettes (e-cigarettes) are products that deliver a nicotine-containing aerosol (commonly called vapor) to users by heating a solution typically made up of propylene glycol or glycerol (glycerin), nicotine, and flavoring agents (Figure 1) invented in their current form by Chinese pharmacist Hon Lik in the early 2000s. The US patent application describes the e-cigarette device as “an electronic atomization cigarette that functions as substitutes [sic] for quitting smoking and cigarette substitutes” (patent No. 8,490,628 B2). By 2013, the major multinational tobacco companies had entered the e-cigarette market. E-cigarettes are marketed via television, the Internet, and print advertisements (that often feature celebrities) as healthier alternatives to tobacco smoking, as useful for quitting smoking and reducing cigarette consumption, and as a way to circumvent smoke-free laws by enabling users to “smoke anywhere. ” There has been rapid market penetration of e-cigarettes despite many unanswered questions about their safety, efficacy for harm reduction and cessation, and total impact on public health. E-cigarette products are changing quickly, and many of the findings from studies of older products may not be relevant to the assessment of newer products that could be safer and more effective as nicotine delivery devices. In addition, marketing and other environmental influences may vary from country to country, so patterns of use and the ultimate impact on public health may differ. The individual risks and benefits and the total impact of these products occur in the context of the widespread and continuing availability of conventional cigarettes and other tobacco products, with high levels of dual use of e-cigarettes and conventional cigarettes at the same time among adults and youth. It is important to assess e-cigarette toxicant exposure and individual risk, as well as the health effects, of e-cigarettes as they are actually used to ensure safety and to develop an evidence-based regulatory scheme that protects the entire population—children and adults, smokers and nonsmokers—in the context of how the tobacco industry is marketing and promoting these products. Health claims and claims of efficacy for quitting smoking are unsupported by the scientific evidence to date. To minimize the potential negative impacts on prevention and cessation and the undermining of existing tobacco control measures, e-cigarette use should be prohibited where tobacco cigarette use is prohibited, and the products should be subject to the same marketing restrictions as tobacco cigarettes.
LOCAL ISOMETRIES OF L ( X, C ( K ))

In this paper we study the structure of local isometries on L ( X,C ( K )). We show that when K is ﬁrst countable and X is uniformly convex and the group of isometries of X ∗ is algebraically reﬂexive, the range of a local isometry contains all compact operators. When X is also uniformly smooth and the group of isometries of X ∗ is algebraically reﬂexive, we show that a local isometry whose adjoint preserves extreme points is a C ( K )-module map.
Cangrelor or Abciximab as€First Choice in Cardiogenic Shock

role of LL-TS may be due to the decreased inflammatory responses, which has been validated by both basic and clinical studies. The intensity of stimulation we used is well below that which slows heart rate and atrioventricular conduction, both standard “parasympathetic” responses. Furthermore, studies have shown that vasostatin-1, rather than the parasympathetic neurotransmitter acetylcholine, mediates the cardioprotective effects of LL-TS or LL vagus nerve stimulation (2). In addition, based on previous studies, LL-TS is antiadrenergic, through a nitric oxide–dependent way (3,4). With regard to the selection of right or left tragus, we think that TS, no matter at the right or the left side, first activates the afferent nerve and transmits signals to the nucleus tractus solitaries, which integrates afferent information and further projects processed signals to the heart through bilateral efferent cervical vagal nerves. Therefore, we suggest that electrical stimulation at the leftor right-sided tragus may exert similar cardioprotective effects. Relative to the duration for the cardioprotective effects of LL-TS, it has been demonstrated that transcutaneous vagus nerve stimulation (120/s and 3 times a day) could reduce serum inflammatory cytokine levels at 24 h after initial stimulation in healthy volunteers (5). We are registering a prospective, multicenter, and randomized clinical trial, and believe this trial will provide more definitive evidence for the cardioprotective effects of LL-TS in STEMI patients.
The Neurorobotics Platform: virtual bodies for biologically realistic brain models and vice versa

—The Neurorobotics Platform is a simulation software aimed at facilitating mutual interactions between robotics and neuroscientiﬁc studies. This tool allows roboticists and neuroscientists to ﬁll the gap between the two disciplines by easing the job of connecting brain simulations with embodiments. This tool could enable a paradigm shift in neurorobotics. In this work, we focus on describing key features of the NRP and few examples on how the NRP can be used to perform neurorobotics research.
EVALUATION OF THE METRIC TRIFOCAL TENSOR FOR RELATIVE THREE-VIEW ORIENTATION

In photogrammetry and computer vision the trifocal tensor is used to describe the geometric relation between projections of points in three views. In this paper we analyze the stability and accuracy of the metric trifocal tensor for calibrated cameras. Since a minimal parameterization of the metric trifocal tensor is challenging, the additional constraints of the interior orientation are applied to the well-known projective 6-point and 7-point algorithms for three images. The experimental results show that the linear 7-point algorithm fails for some noise-free degenerated cases, whereas the minimal 6-point algorithm seems to be competitive even with realistic noise.
Randomized trial of three chemotherapy regimens and two radiotherapy regimens in postoperative treatment of malignant glioma

Within 3 weeks of definitive surgery, 571 adult patients with histologically confirmed, supratentorial malignant gliomas were randomly assigned to receive one of three chemotherapy regimens: BCNU (1,3-bis(2-chloroethyl)-1-nitrosourea) alone, alternating courses (every 8 weeks) of BCNU and procarbazine, or BCNU plus hydroxyurea alternating with procarbazine plus VM-26 (epipodophyllotoxin). Patients accrued in 1980 and 1981 were to receive 6020 rads of whole-brain radiotherapy concurrent with the first course of chemotherapy. Patients accrued in 1982 and 1983 were randomly assigned to receive either whole-brain irradiation as above, or 4300 rads of whole-brain radiotherapy plus 1720 rads coned down to the tumor volume. The data were analyzed for the total randomized population and separately for the 510 patients, termed the “Valid Study Group (VSG),” who met protocol eligibility specifications (including central pathology review), 80% of whom had glioblastoma multiforme. The median survival times from time .
Scalable Resource Provisioning in the Cloud Using Business Metrics

—Currently cloud infrastructures are in the spot-light of computer science. Through offering on-demand resource provisioning capabilities and high ﬂexibility of management cloud-based systems can seamlessly adjust to the constantly changing environment of the Internet. They can automatically scale according to a chosen policy. Despite the usefulness of the currently available tools in this area there is still much space for improvements. In this paper we introduce a novel approach to automatic infrastructure scaling, based on the observation of business-related metrics. We present details on a tool based on this concept, which uses a semantic-based monitoring and management system, called SAMM. At the end we discuss the capabilities of the new mechanisms.
Institutional Knowledge at Singapore Management University Institutional Knowledge at Singapore Management University Sherlock: Microenvironment sensing for smartphones Sherlock: Microenvironment sensing for smartphones

—Context-awareness is getting increasingly important for a range of mobile and pervasive applications on nowadays smartphones. Whereas human-centric contexts (e.g., indoor/ outdoor, at home/in ofﬁce, driving/walking) have been extensively researched, few attempts have studied from phones’ perspective (e.g., on table/sofa, in pocket/bag/hand). We refer to such immediate surroundings as micro-environment , usually several to a dozen of centimeters, around a phone. In this study, we design and implement Sherlock, a micro-environment sensing platform that automatically records sensor hints and characterizes the micro-environment of smartphones. The platform runs as a daemon process on a smartphone and provides ﬁner-grained environment information to upper layer applications via programming interfaces. Sherlock is a uniﬁed framework covering the major cases of phone usage, placement, attitude, and interaction in practical uses with complicated user habits. As a long-term running middleware, Sherlock considers both energy consumption and user friendship. We prototype Sherlock on Android OS and systematically evaluate its performance with data collected on ﬁfteen scenarios during three weeks. The preliminary results show that Sherlock achieves low energy cost, rapid system deployment, and competitive sensing accuracy.