Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Study of the Adsorption of Lead and Cadmium by Activated Carbon from Jatropha curcas and Moringa Husk

Moringa husks and Jatropha cacus were evaluated using decoloration of methylene blue for the removal of lead (Pb) and cadmium (Cd) from water sample. The results showed that Moringa has better properties: physicochemical properties: pH, moisture content (%), ash content (%), carbon content (%), volatile matter (%), surface area (m2/g), electrical conductivity (µs/cm), bulk and density (g/L), 6.4, 14, 4, 63.26, 10, 787, 867 and 400 respectively, decoloration of methylene blue at 10 to 90 minutes ranges from 11 to 87% , Pb and Cd adsorption capacity 55.7 and 86, % degradation 85 and 92 than the Jatropha cacus 50.2 and 55.2, 78 and 83 respectively. The Moringa husk was characterized using Fourier Transform Infrared (FTIR), Scanning Electron Microscope (SEM) and its adsorption properties were studied by Langmuir and Freundlich kinetic isotherms.
Biomarker of Neuroinflammation in Parkinson’s Disease

Parkinson’s disease (PD) is caused by abnormal accumulation of α-synuclein in dopaminergic neurons of the substantia nigra, which subsequently causes motor symptoms. Neuroinflammation plays a vital role in the pathogenesis of neurodegeneration in PD. This neuroinflammatory neurodegeneration involves the activation of microglia, upregulation of proinflammatory factors, and gut microbiota. In this review, we summarized the recent findings on detection of PD by using inflammatory biomarkers, such as interleukin (IL)-1β, IL-2, IL-6, IL-10, tumor necrosis factor (TNF)-α; regulated upon activation, normal T cell expressed and presumably secreted (RANTES) and high-sensitivity c-reactive protein (hsCRP); and radiotracers such as [11C]PK11195 and [18F]-FEPPA, as well as by monitoring disease progression and the treatment response. Many PD-causing mutations in SNCA, LRRK2, PRKN, PINK1, and DJ-1 are also associated with neuroinflammation. Several anti-inflammatory medications, including nonsteroidal anti-inflammatory drugs (NSAID), inhibitors of TNF-α and NLR family pyrin domain containing 3 (NLRP3), agonists of nuclear factor erythroid 2-related factor 2 (NRF2), peroxisome proliferator-activated receptor gamma (PPAR-γ), and steroids, have demonstrated neuroprotective effects in in vivo or in vitro PD models. Clinical trials applying objective biomarkers are required to investigate the therapeutic potential of anti-inflammatory medications for PD.
Parasitic flowering plant collections embody the extended specimen

The widespread digitization of natural history collections, combined with novel tools and approaches is revolutionizing biodiversity science. The ‘extended specimen’ concept advocates a more holistic approach in which a specimen is framed as a diverse stream of interconnected data. Herbarium specimens that by their very nature capture multispecies relationships, such as certain parasites, fungi and lichens, hold great potential to provide a broader and more integrative view of the ecology and evolution of symbiotic interactions. This particularly applies to parasite–host associations, which owing to their interconnectedness are especially vulnerable to global environmental change. Here, we present an overview of how parasitic flowering plants is represented in herbarium collections. We then discuss the variety of data that can be gathered from parasitic plant specimens, and how they can be used to understand global change impacts at multiple scales. Finally, we review best practices for sampling parasitic plants in the field, and subsequently preparing and digitizing these specimens. Plant parasitism has evolved 12 times within angiosperms, and similar to other plant taxa, herbarium collections represent the foundation for analysing key aspects of their ecology and evolution. Yet these collections hold far greater potential. Data and metadata obtained from parasitic plant specimens can inform analyses of co‐distribution patterns, changes in eco‐physiology and species plasticity spanning temporal and spatial scales, chemical ecology of tripartite interactions (e.g. host–parasite–herbivore), and molecular data critical for species conservation. Moreover, owing to the historic nature and sheer size of global herbarium collections, these data provide the spatiotemporal breadth essential for investigating organismal response to global change. Parasitic plant specimens are primed to serve as ideal examples of extended specimen concept and help motivate the next generation of creative and impactful collection‐based science. Continued digitization efforts and improved curatorial practices will contribute to opening these specimens to a broader audience, allowing integrative research spanning multiple domains and offering novel opportunities for education.
How to Drive Drivers Nuts: Effect of Auditory, Vibrotactile, and Multimodal Warnings on Perceived Urgency, Annoyance, and Acceptability

With semiautonomous vehicles and innovative assistance systems flooding the market, the characteristics of warning signals for automotive human–machine interfaces determine their effectiveness and usage. Within the context of advanced driver assistance systems, poorly designed warning signals have the potential to startle and distract drivers. Previous studies have investigated the effectiveness of multimodal warning signals and found that such signals reduce braking times. They are also associated with high levels of perceived urgency. This study aimed to investigate the effects of auditory, vibrotactile, and multimodal warning signals on perceived urgency, annoyance, and acceptability while varying the level of participants’ mental workload and the characteristics of the warning signals (interpulse interval). Results show that, compared with other signal modalities, multimodal warning signals appear to be effective in low-workload conditions but such effect disappears as the overall level of workload increases. These results are useful for the development of an adaptive warning signal system.
Predicting neuromuscular control patterns that minimize ACL forces during injury-prone jump-landing manoeuvres in downhill skiing using a musculoskeletal simulation model

ABSTRACT Competitive skiers encounter a high risk of sustaining an ACL injury during jump-landing in downhill ski racing. Facing an injury-prone landing manoeuvre, there is a lack of knowledge regarding optimum control strategies. So, the purpose of the present study was to investigate possible neuromuscular control patterns to avoid injury during injury-prone jump-landing manoeuvres. A computational approach was used to generate a series of 190 injury-prone jump-landing manoeuvres based on a 25-degree-of-freedom sagittal plane musculoskeletal skier model. Using a dynamic optimization framework, each injury-prone landing manoeuvre was resolved to identify muscle activation patterns of the lower limbs and corresponding kinematic changes that reduce peak ACL force. In the 190 injury-prone jump-landing simulations, ACL forces peaked during the first 50 ms after ground contact. Optimized muscle activation patterns, that reduced peak ACL forces, showed increased activation of the monoarticular hip flexors, ankle dorsi- and plantar flexors as well as hamstrings prior to or during the early impact phase (<50 ms). The corresponding kinematic changes were characterized by increased hip and knee flexion and less backward lean of the skier at initial ground contact and the following impact phase. Injury prevention strategies should focus on increased activation of the monoarticular hip flexors, ankle plantar flexors and rapid and increased activation of the hamstrings in combination with a flexed landing position and decreased backward lean to reduce ACL injury risk during the early impact phase (<50 ms) of jump landing. Highlights First study investigating advantageous control strategies during injury-prone jump-landing manoeuvres in downhill skiing using a musculoskeletal simulation model and dynamic optimization framework. The simulation results predicted high injury risk during the first 50 ms after initial ground contact. Optimized neuromuscular control patterns showed adapted activation patterns (timing and amplitude) of muscles crossing the knee as well as the hip and ankle joints prior to and after initial ground contact, respectively. An optimized control strategy during an injury-prone landing manoeuvre was characterized kinematically by increasing hip and knee flexion and less backward lean of the skier at initial ground contact and the following impact phase.
Rethinking Distribution: Introducing Market Segmentation as a Policy Instrument 1

Inequality and skewed distribution of ‘essential’ goods remain problems even in the 21st-century world. We consider a general equilibrium framework where some goods are considered essential, whereas some are not. Essential goods are relevant for distributional concerns, up to a certain level of consumption. We then compare the eﬀects of four policies on social welfare: subsidies, direct transfers, quantity rationing, and a fourth policy that we introduce and call Market Segmentation (MS) . In MS, the market for essentials is segmented from non-essentials, i.e. they are not freely tradeable with each other. We ﬁnd that if the relative number of low-income individuals in the economy is large and “essentials” are consumed in-elastically, MS outperforms direct transfers and subsidies. We also show that in our model, MS weakly dominates quantity rationing. We discuss how market segmentation can help policymakers to deal with issues such as automation and superstar phenomenon (Scheuer and Werning, 2017).
PTT_A_294189 35..51

Objective: To evaluate the effect of lifestyle changes on the severity of psoriasis and the quality of life in patients with psoriasis. Methods: For this narrative review, PubMed, Embase and ClinicalTrials.gov were searched for lifestyle intervention studies with an intervention duration of at least 12 weeks. Results: Thirty-four intervention studies were included. Most studies performed interventions in the diet of patients with psoriasis (n=9), or added supplements to the diet (n=18). Three studies comprised relaxation techniques and four studies combined relaxation or stress-reducing techniques with an educational program or exercise. No interventional studies were carried out regarding smoking, alcohol and sleep. Especially dietary and relaxation interventions showed promising results with respect to psoriasis severity and dermatology-related QoL, respectively. Regarding dietary supplements, the three largest studies investigating fish oil or vitamin D did not show significant effects. Conclusion: There is some evidence that dietary and relaxation interventions could be promising with respect to psoriasis severity and dermatology-related QoL, respectively. Furthermore, our review identified important gaps in psoriasis lifestyle research regarding study design and reporting of outcomes.
Optimal age-replacement policy for non-repairable technical objects with warranty

In order to obtain maintenance system reliability and availability, preventive replacements according to the age of elements and subsystems are introduced into the maintenance system. Age-replacements have been known for a long time, e.g. [2]. This problem was examined through development of preventive age-replacement for various individual cases. In particular, in the papers [3, 4, 10, 12] whole range of important analytical results was obtained. However, the methods of age-replacement for technical objects with valid manufacturer’s warranty were developed much later. Currently, manufacturer’s warranty is a basic element of modern market. The basic role of a warranty is an offer including a list of actions the customer must undertake when the product is damaged during warranty period. Manufacturer’s warranty for the product creates an incentive for the customer to make various commitments, improving the reputation of the manufacturer, and influencing the market share as well as potential profit. A detailed discussion and overview of the results connected to various approaches to product warranty is included in the following papers [5, 6, 7]. In particular, the warranty policy for non-repairable products was discussed in the paper [5]. The warranty policy analyzed in this paper is carried out through the strategy of damaged element replacement within the period of warranty by a new element with full warranty. The mathematical model and cost analysis for such strategy were developed in the papers [1, 8, 13]. In the paper [14] the criteria function defining the costs connected to carrying out preventive replacements of non-repairable elements with a warranty when time before failure has distribution with increasing failure rate function. In the quoted paper the criteria function depends on the distribution of time before failure, repair and preventive replacement costs as well as the length of warranty period. It is assumed that the times of repair and preventive replacement are negligible. In this paper the criteria function discussed is more general than in the paper [14], taking into consideration non-zero times of repair and times of preventive replacements. The set-up of the criteria function g(x) was based on the limit values of semi–Markov processes. The aim of this work is to formulate the conditions for existence of minimum function g(x) defining losses in maintenance system.
FlakiMe: Laboratory-Controlled Test Flakiness Impact Assessment

Much research on software testing makes an implicit assumption that test failures are deterministic such that they always witness the presence of the same defects. However, this assumption is not always true because some test failures are due to so-called flaky tests, i.e., tests with non-deterministic outcomes. To help testing researchers better investigate flakiness, we introduce a test flakiness assessment and experimentation platform, called FlakiMe. FlakiMe supports the seeding of a (controllable) degree of flakiness into the behaviour of a given test suite. Thereby, FlakiMe equips researchers with ways to investigate the impact of test flakiness on their techniques under laboratory-controlled conditions. To demonstrate the application of FlakiMe, we use it to assess the impact of flakiness on mutation testing and program repair (the PRAPR and ARJA methods). These results indicate that a 10% flakiness is sufficient to affect the mutation score, but the effect size is modest (2% – 5%), while it reduces the number of patches produced for repair by 20% up to 100% of repair problems; a devastating impact on this application of testing. Our experiments with FlakiMe demonstrate that flakiness affects different testing applications in very different ways, thereby motivating the need for a laboratory-controllable flakiness impact assessment platform and approach such as FlakiMe.
HyporesponsivenessHuman Liver Dendritic Cells Promote T Cell

The liver is believed to promote tolerance, which may be beneﬁcial due to its constant exposure to foreign Ags from the portal circulation. Although dendritic cells (DCs) are critical mediators of immune responses, little is known about human liver DCs. We compared freshly puriﬁed liver DCs from surgical specimens with autologous blood DCs. Liver and blood DCs were equally immature, but had distinct subset compositions. BDCA-1 (cid:1) DCs represented the most prevalent liver DC subset, whereas the majority of peripheral blood DCs were CD16 (cid:1) . Upon TLR4 ligation, blood DCs secreted multiple proinﬂammatory cytokines, whereas liver DCs produced substantial amounts of IL-10. Liver DCs induced less proliferation of allogeneic T cells both in a primary MLR and after restimulation. Similarly, Ag-speciﬁc CD4 (cid:1) T cells were less responsive to restimulation when initially stimulated by autologous liver DCs rather than blood DCs. In addition, liver DCs generated more suppressive CD4 (cid:1) CD25 (cid:1) FoxP3 (cid:1) T regulatory cells and IL-4-producing Th2 cells via an IL-10-dependent mechanism. Our ﬁndings are critical to understanding hepatic immunity and demonstrate that human liver DCs promote immunologic hyporesponsiveness that may contribute to hepatic tolerance. The Journal of Immunology, 2009, 182: 1901–1911. A robust overall
Coronavirus Pandemic Association of SARS-CoV-2 cycle threshold (Ct) values with clinical course and serum biomarkers in COVID-19 patients

Introduction: Our knowledge has gaps regarding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication levels and its association to severity of Coronavirus disease 2019 (COVID-19). The aim of this study was to investigate the association of SARS-CoV-2 viral load with disease severity and serum biomarkers in COVID-19 patients. Methodology: Viral load was determined via cycle threshold (Ct) values of SARS-CoV-2 real-time reverse transcriptase-polymerase chain reaction (RT-PCR) in 214 adult patients. Ct values were compared with clinical severity, biochemical and hematological biomarkers. Results: Clinical course of the disease was mild (49.1%), moderate (40.2%), and severe (10.7%). Median Ct value was 28.2 (IQR: 22.2–33.8) during the first week of the disease. Ct values were lower within five days after symptom onset [lowest Ct value on the third day (median: 24, IQR: 20.6–32.3)], but they increased significantly during the second and third weeks. No association was detected between admission Ct values and disease severity. Gender, age, co- morbidity, and mortality did not differ significantly in patients with low (≤ 25) and high (> 25) Ct values. White blood cell, neutrophil, platelet, and especially lymphocyte counts, were significantly lower in patients with low Ct values. Conclusions: No definitive/clear correlation between SARS-CoV-2 viral load and severity and mortality was found in the studied COVID-19 patients. However, neutrophil, platelet, and especially lymphocyte count were significantly lower in patients with a high viral load.
Methods and tools to support New Product Development tasks

Companies have to develop innovative and valuable products in order to achieve competitive advantage. To this aim, the idea generation task should be effectively supported within the Product Planning phase, whose goal is defining the main product features. According to this objective, the paper proposes a tool, namely Four Dimensions framework, that urges designers looking for new customer requirements through the mapping of General Demands, Stakeholders, Life Cycle and Systems. The tool has been simulated through an application to the first Apple iMac (1998), obtaining promising results.
Matrix factorization models for cross-domain recommendation: Addressing the cold start in collaborative filtering

Recommender systems are software tools designed to help users in information access and retrieval tasks. By analyzing previous user interactions with certain information items, these systems estimate the users’ preferences (i.e., tastes, interests and needs) for other items to predict and suggest the most relevant ones. Actively investigated since the nineties, recommender systems have gained popularity and sophistication, and nowadays are essential components of numerous business, education, culture and entertainment services, such as ecommerce sites like Amazon.com and eBay, media content providers like Netflix, YouTube and Spotify, and online social networks like Facebook and Twitter. Multiple recommendation approaches, and remarkably those based on collaborative filtering, have been proposed and successfully implemented over the last years. However, they still have limitations and challenges that in turn represent research opportunities. One of the most notorious of these opportunities is the so called cold start problem, which refers to the situation where a new user has recently registered in a system, and for whom there are not enough preferences to deliver relevant personalized recommendations. Two types of approaches have been explored to address the cold start. The first is represented by techniques that intelligently elicit the preferences from the user, while the second includes methods that make use of additional information to infer user preferences. Within this last type of approaches, cross-domain recommendation has recently emerged as a potential solution, exploiting user preferences and item attributes in domains distinct, but related to the target recommendation domain. Cross-domain recommender systems are currently under research in several fields with particular goals and tasks. In User Modeling, these systems have been proposed as a mechanism to aggregate and mediate user profiles as a cross-system personalization strategy, in Machine Learning they have been explored as a practical application of transfer learning techniques, and in Recommender Systems as a way to mitigate the scarcity of user preference data. This thesis focuses on the study of cross-domain recommender systems as a solution to the cold start. We first provide an in-depth review of the state of the art in the above mentioned research fields, providing a unifying formalization of the problem, and a categorization of existing approaches and evaluation methodologies. We then present three novel adaptations of the matrix factorization technique for cross-domain collaborative filtering. In particular, we propose a number of models that deal with different sources of infor-
University of Birmingham Search-based diverse sampling from real-world software product lines

Real-world software product lines (SPLs) often encompass enormous valid con(cid:12)gurations that are impossible to enumerate. To understand properties of the space formed by all valid con(cid:12)gurations, a feasible way is to select a small, valid and representative sample set. Even though a number of sampling strategies have been proposed, they either fail to produce diverse samples with respect to the number of selected features (an important property to characterize behaviors of con(cid:12)gurations), or achieve diverse sampling but with limited scalability (the handleable con(cid:12)guration space size is limited to 10 13 ). To resolve this dilemma, we propose a scalable diverse sampling strategy, which uses a distance metric in combination with the novelty search algorithm to produce diverse samples in an incremental way. The distance metric is carefully designed to measure similarities between con(cid:12)g-urations, and further diversity of a sample set. The novelty search incrementally improves diversity of samples through the search for novel con(cid:12)gurations. We evaluate our sampling algorithm on 39 real-world SPLs. It is able to generate the required number of samples for all the SPLs, including those which can not be counted by sharpSAT, a state-of-the-art model counting solver. Moreover, it performs better than or at least competitively to some state-of-the-art sam-plers with respect to the diversity of the sample sets. Our results suggest that only the proposed sampler (among all tested ones) achieves scalable diverse sampling.