Miracle-dz/UniFAR-FTUs huggingface dataset:
Ocena stanu ekologicznego rzek i jezior w Wielkopolsce na podstawie makrofitow zgodnie z wymaganiami Ramowej Dyrektywy Wodnej

Streszczenie. Badania makrofitowe prowadzono w latach 2007-2008 w ramach Państwowego Monitoringu Środowiska realizowanego przez Wojewódzki Inspektorat Ochrony Środowiska w Poznaniu. Badania jezior wykonano, wykorzystując Makrofitowy Indeks Stanu Ekologicznego Jezior. W odniesieniu do rzek zastosowano Makrofitową Metodę Oceny Rzek. Przebadano łącznie 26 jezior oraz 81 stanowisk na 53 rzekach na obszarze województwa wielkopolskiego. Badania realizowane na jeziorach wykazały, że 4 jeziora są w bardzo dobrym stanie ekologicznym, 11 w dobrym, 7 w umiarkowanym, 3 w słabym oraz 1 w złym. Według wyników badań wody płynące Wielkopolski reprezentują pełny gradient stanu ekologicznego i zostały zaklasyfikowane do wszystkich pięciu kategorii. Stwierdzono, że bardzo dobry stan wykazuje 5 stanowisk, dobry – 43, umiarkowany – 22, słaby – 8, a zły – 3. Przeprowadzone badania dowiodły, że metody makrofitowe mogą być stosowane do oceny wszystkich typów wód występujących w Wielkopolsce (oprócz silnie zmienionych części wód), a liczba gatunków roślin wodnych oraz zbiorowisk roślinnych była zawsze dostateczna do określania stanu ekologicznego.
Deep Distributional Temporal Di↵erence Learning for Game Playing

Temporal di↵erence learning is considered one of the most successful methods in reinforcement learning. Recent developments in deep learning have opened up a new world of opportunities. In this project, we compare classic scalar temporal di↵erence learning with three new distributional algorithms for playing the game of 5-in-a-row using deep neural networks: distributional temporal di↵erence learning with constant learning rate, and two distributional temporal di↵erence algorithms with adaptive learning rate. All these algorithms are applicable to any two-player deterministic zero sum game and can probably be successfully generalized to other settings. As it turned out, all algorithms performed well and developed strong strategies. The algorithms implementing the adaptive methods learned more quickly in the beginning, but in the long run, they were outperformed by the algorithms using constant learning rate which, without any prior knowledge, learned to play the game at a very high level after 200 000 games of self play.
Prepare or Go: An analysis of enforcing tutorial preparation requirements in an accounting course

The tutorial is often seen as the primarily vehicle that provides students with the opportunity to actively engage with the subject materials, their teacher and their peers. Although preparation for class is an expectation, students’ lack of preparation for tutorial work is widespread. This results in a reality where not only the unprepared student’s engagement is problematic but the experiences of their peers and the ability of teaching academics to facilitate learning is also compromised. Within an action research approach, this paper discusses the rationale, implementation and results of requiring students to provide evidence of adequate class preparation in order to attend tutorials for a financial accounting course. This requirement transformed the nature of tutorials although it had no impact on student evaluations or results.
n° 2012-30 Wars as Large Depreciation Shocks

In this paper, we propose a theoretical framework to investigate the impact of conﬂicts and wars on key macroeconomic aggregates and welfare. Using a panel data with 12 countries from 1875 onwards we ﬁrst show that consumption drops more than output during conﬂicts, while the opposite is true during “peaceful” recessions. To handle both cases, we build a variation of a Real Business Cycle model ﬁrst proposed by Hercowitz and Sampson [1991]. We extend the initial model to account for speciﬁc shocks that destroy capital stocks – as conﬂicts do– by assuming an (exogenously) time–varying depreciation rate of the stock of capital. In addition to these shocks, the model also imbeds generalized TFP shocks capturing standard technological factors as well as the potential eﬀects of human losses on production. The model is able to reproduce the diﬀerent responses of macroeconomic aggregate to productivity shocks during peaceful periods as well as their responses during conﬂicts. We describe how these two sources of randomness in the model may be extracted from the available data, and analyze how they interact. We conclude that conﬂicts have signiﬁcant and persistent inﬂuence on generalized TFP shocks, while the “reverse” eﬀect is not statistically signiﬁcant. Finally, we show that the welfare costs of conﬂicts such as World War II are substantially larger than the welfare costs of business cycles usually reported in the literature.
University of Birmingham The drilling of carbon fibre composite-aluminium stacks and its effect on hole quality and integrity

The paper details experimental work to evaluate tool wear, cutting forces/torque and associated hole quality/accuracy following single-shot drilling of twin layer CFRP/AA7010 stacks. A full factorial experiment was initially planned involving variation in cutting speed (60 and 120 m/min), feed rate (0.15 and 0.30 mm/rev) and drill tip geometry (double cone and flat point drills). While flank wear for the flat point drills did not exceed 40 µm even after 120 holes irrespective of operating conditions, the double cone geometry suffered catastrophic failure after only 4 holes at the lowest parameter combination. Therefore, the remaining tests involving the double cone drill at higher operating parameters were subsequently halted. Feed rate had a significant influence on torque in both the CFRP and Al layers, although thrust force and torque generally remained stable over the test duration. Hole diameter was typically up to 34 µm above the nominal value of 6.38 mm with corresponding out of roundness of < 60 µm. Burrs were prevalent at hole exit in all tests, with an average height of ~120 µm when drilling at the highest cutting speed-feed rate parameter combination. Similarly, the delamination factor at hole entry increased by up to 23% when operating at the higher feed rate level.
Scandinavian Journal of Pain

Objectives: Cognitive inhibition, which denotes the ability to suppress predominant or automatic responses, has been associated with lower pain sensitivity and larger conditioned pain modulation in humans. Studies exploring the association between cognitive inhibition and other pain inhibitory phenomena, like exercise-induced hypoalgesia (EIH), are scarce. The primary aim was to explore the association between cognitive inhibition and EIH at exercising (local) and non-exercising (remote) muscles after isometric exercise. The secondary aim was to explore the association between cognitive inhibition andpressure pain sensitivity. Methods: Sixty-six pain-free participants (28.3 ± 8.9 years old, 34 women) completed two cognitive inhibition tasks (stop-signal task and Stroop Colour-Word task), a 3-min isometric wall squat exercise, and a quiet rest control condition with preand post-assessments of manual pressure pain thresholds at a local (thigh) and a remote site (shoulder). In addition, cuff pressure pain thresholds, pain tolerance and temporal summation of pain were assessed at baseline. Results: No association was found between remote EIH and cognitive inhibition (Stroop interference score: r=0.12, [−0.15; 0.37], p=0.405, BF01=6.70; stop-signal reaction time: r=−0.08, [−0.32; 0.17], p=0.524, BF01=8.32). Unexpectedly, individuals with worse performance on the Stroop task, as indicated by a higher Stroop interference score, showed higher local EIH (r=0.33; [0.10; 0.53], p=0.007, BF01=0.29). No associations were observed between pain sensitivity and any of the cognitive inhibition performance parameters. Conclusions: The present findings do not support previous evidence on positive associations between exerciseinduced hypoalgesia and cognitive inhibition, as well as baseline pain sensitivity and cognitive inhibition.
Designing-related neural processes: Higher alpha, theta and beta bands’ key roles in distinguishing designing from problem-solving

This paper presents results from an experiment studying differences be-tween designing and problem-solving in professional industrial designers, using EEG to measure neurophysiological activations. We compare neurophysiological activation and frequency bands power between three pro-totypical tasks, a problem-solving layout task, an open design layout task and an open design free-hand sketching task. The study draws on the neurophysiological results from 18 experiment sessions with professional designers. Results indicate significant differences in activations between the problem-solving task and the design tasks, in terms of aggregate, temporal and frequency bands power across participants. Higher alpha and beta frequency band values play a key role in the open design sketching task when compared to the layout tasks.
A Neglected Narrative in the COVID-19 Pandemic: Epidemiological and Clinical Impacts of the COVID-19 Outbreak on Syphilis

Abstract The COVID-19 pandemic has profoundly changed our lives. While healthcare resources were redistributed and mobilized to focus on dealing with the COVID-19 crisis, there have been unmet medical needs of patients with other diseases such as syphilis, weaving an integral but neglected component of the pandemic story. In different countries, the epidemiology of newly reported syphilis underwent diverse changes during the COVID-19 pandemic. Asymptomatic cases experienced the largest decline in number. From the perspective of transmission, on one hand, the implementation of lockdown measures led to a higher degree of abstinence and sex distancing in many countries, thereby reducing the transmission of syphilis. On the other hand, vertical transmission was reported to have increased significantly during COVID-19. Meanwhile, the volume of STI clinic capacity declined, and STI staff were redeployed to facilitate the contact tracing of COVID-19. As a result, many STI centers converted traditional in-person clinical services to telemedicine and self-testing. However, syphilis testing and clinical treatment cannot fully adapt to this conversion. In syphilis diagnosis, COVID-19 infection and vaccination were reported to cause false positivity in syphilis serological tests. Diverse cutaneous manifestations of COVID-19 could resemble the skin lesions in syphilis patients, requiring differential diagnosis from clinicians. As for the post-pandemic years, consequent to service interruptions and diagnosis delays, a surge in the number of confirmed cases of syphilis is expected. The COVID-19 pandemic has also been a meaningful lesson for the control and prevention of infectious diseases. The experience in combating COVID-19 has underscored the importance of maintaining a robust and well-supported medical system for the provision of sexual health services and better healthcare equality even during eras of crisis, not least for syphilis patients.
A New Approach for Classifying Two Types of El Niño Events

Abstract In recent decades, the typical El Niño events with the warmest SSTs in the tropical eastern Pacific have become less common, and a different of El Niño with the warmest SSTs in the central Pacific, which is flanked on the east and west by cooler SSTs, has become more frequent. The more recent type of El Niño was referred to as central Pacific El Niño, warm pool El Niño, or dateline El Niño, or the El Niño Modoki. Central Pacific El Niño links to a different tropical-to-extratropical teleconnection and exerts different impacts on climate, and several classification approaches have been proposed. In this study, a new classification approach is proposed, which is based on the linear combination (sum or difference) of the two leading Empirical Orthogonal Functions (EOFs) of tropical Pacific Ocean sea surface temperature anomaly (SSTA), and the typical El Niño index (TENI) and the central El Niño index (CENI) are able to be derived by projecting the observed SSTA onto these combinations. This classification not only reflects the characteristics of non-orthogonality between the two types of events but also yields one period peaking at approximate two to seven years. In particular, this classification can distinguish the different impacts of the two types of events on rainfall in the following summer in East China. The typical El Niño events tend to induce intensified rainfall in the Yangtze River valley, whereas the central Pacific El Niño tends to induce intensified rainfall in the Huaihe River valley. Thus, the present approach may be appropriate for studying the impact of different types of El Niño on the East Asian climate.
Random Slicing: Efﬁcient and Scalable Data Placement for Large-scale Storage Systems

The ever-growing amount of data requires highly scalable storage solutions. The most ﬂexible approach is to use storage pools that can be expanded and scaled down by adding or removing storage devices. To make this approach usable, it is necessary to provide a solution to locate data items in such a dynamic environment. This paper presents and evaluates the Random Slicing strategy, which incorporates lessons learned from table-based, rule-based, and pseudo-randomized hashing strategies and is able to provide a simple and eﬃcient strategy that scales up to handle exascale data. Random Slicing keeps a small table with information about previous storage system insert and remove operations, drastically reducing the required amount of randomness while delivering a perfect load distribution.
Agroecosystems of South India: Nutrient Dynamics, Ecology and Productivity

contents: History of Southern Indian agriculture and agroecosystems; Agroecosystems of South India: an introduction; Rice agroecosystem of South India: nutrient dynamics, ecology and productivity; Sorghum agroecosystem of South India: nutrients, ecology and productivity Maize belt of South India: nutrients, ecology and productivity; Finger millet cropping zones of South India: nutrients, ecology and productivity;Legumes agroecosystem of South India: nutrients, ecology and productivity Groundnut agroecosystem of South India: nutrient dynamics, ecology and productivity; Sunflower agroecosystem of South India: nutrient dynamics and productivity.
University of Birmingham 3C framework for modular supply networks in the Chinese automotive industry

Purpose – This paper aims to understand and identify the context, capability requirements and configurations of the modular supply network in the Chinese automotive industry. Design/Methodology/Approach – In an attempt to specify the main elements of the modular supply network, a case study and 3C framework approach are used to analyze the different contexts of the network. The framework not only considers the capabilities of product design, production, inbound logistics and information sharing but also considers the configuration of role structure, process structure and information structure to achieve the above capabilities. Findings – The paper analyzes two types of modular supply network, directly reflecting the degree of involvement in the modularity logic of the module supplier and the automaker, which largely depends on their corporate strategy regarding technology innovation. Within the fully integrated module supply network, the module supplier needs sufficient capability for upstream supply network integration as well as modularization, while in the partly integrated module supply network, a 3PL provider plays an important role regarding production capability. Research limitations/implications – Four modules are investigated in this study. The practical tools for configuring the modular supply network will be specified in more detail in future research. Practical implications – With the emerging M&A operations of the component supplier, modular supply has become dominate in the Chinese automotive industry. The modular supply network increasingly relies on the establishment of the capabilities of the key roles in the network configuration. The 3C framework suggests a method for practitioners to improve the performance of the modular supply network. Originality/value – The 3C framework described in this paper contributes to theory in not only the field of supply chain management but also to modularity, and it assists in further expanding the theory of SCM as well.
Monomorphic Post-Transplant Lymphoproliferative Disorder in Pediatric Solid Organ Transplant Recipients: Treatment Approach Across Canada

There are no standardized pediatric treatment protocols for monomorphic post-transplant lymphoproliferative disorder (PTLD). We reviewed data from Canadian pediatric centers to determine patient characteristics, treatment approaches and outcomes. There were 55 eligible children diagnosed with monomorphic PTLD between January 2001-December 2021. Forty-nine (89%) underwent reduction of immunosuppression. The majority, 44 (80%), received rituximab, 40/44 (91%) with concurrent chemotherapy. A total of 46 (84%) children received chemotherapy: LMB-96 (48%) and low-dose cyclophosphamide with prednisone (30%) being the favored regimens. Projected 3-year event-free survival and overall survival was 62% and 77%, respectively. Approach to monomorphic PTLD treatment was relatively consistent across Canada.
Cardiorespiratory ﬁtness effect may be under-estimated in ‘fat but ﬁt’ hypothesis studies

Background: Both cardiorespiratory fitness and body fat have been independently related to metabolic syndrome in adolescents; however, the strength of these relationships seems to be dependent on the outcome composition. Aim: To analyse the relationship between cardiorespiratory fitness and body fat combined with different indicators of metabolic risk in adolescents. Subjects and methods: The sample was composed of 957 adolescents (58.7% girls). Cardiorespiratory fitness was obtained using the 20-metre shuttle run test and skinfold thickness was collected for body fat estimation. Metabolic risk score was calculated from waist circumference, systolic and diastolic blood pressure, glucose, HDL cholesterol and triglycerides measurements and an alternative outcome without the central obesity indicator was adopted. Chronological age and somatic maturity were used as covariates. Results: Higher metabolic risk was observed in the highest fat/lowest fit adolescents ( p < .05), regardless of sex and outcome. In the regression models, for full metabolic risk score, body fat presented higher coefficients compared to cardiorespiratory fitness in both sexes (boys: 0.501 vs (cid:1) 0.097; girls: 0.485 vs (cid:1) 0.087); however, in the metabolic risk without waist circumference, the coefficients became closer (boys: 0.290 vs (cid:1) 0.146; girls: 0.265 vs (cid:1) 0.120), with a concomitant decrease in body fat and increase in cardiorespiratory fitness coefficients. Conclusion: These findings suggest that body fat is strongly related to cardiovascular risk, but, when the outcome is calculated without the central obesity indicator, cardiorespiratory fitness becomes more related to metabolic risk.
Advanced Data Expoitation in Speech Analysis

W ith recent advances in machine-learning techniques for automatic speech analysis (ASA)—the computerized extraction of information from speech signals—there is a greater need for high-quality, diverse, and very large amounts of data. Such data could be game-changing in terms of ASA system accuracy and robustness, enabling the extraction of feature representations or the learning of model parameters immune to confounding factors, such as acoustic variations, unrelated to the task at hand. However, many current ASA data sets do not meet the desired properties. Instead, they are often recorded under less than ideal conditions, with the corresponding labels sparse or unreliable. In addressing these issues, this article provides a comprehensive overview of state-of-the-art ASA data exploitation techniques that have been developed to take advantage of knowledge gained from related but unlabeled or different data sources to improve the performance of a particular ASA task of interest. We first identify three primary data challenges: sparse, unreliable, and unmatched data. We then review the corresponding approaches. The conditions, advantages, and drawbacks of using a range of differing data-mining techniques are also discussed. Finally, other data challenges and potential future research directions in this field are presented.
A Knowledge-Level Account of Abduction

In this paper, we consider a new definition of abduction that makes it depend on an underlying formal model of belief. In particular, different models of belief will give rise to different forms of abductive reasoning. Based on this definition, we then prove three main theorems: first, that when belief is closed under logical implication, the corresponding form of abduction is precisely what is performed by the ATMS as characterized by Reiter and de Kleer; second, that with the more limited "explicit" belief defined by Levesque, the required abduction is computationally tractable in certain cases where the ATMS is not; and finally, that something is believed in the implicit sense iff repeatedly applying a limited abduction operator eventually yields something that is believed in the explicit sense. This last result relates deduction and abduction as well as limited and unlimited reasoning all within the context of a logic of belief.
CROWDFUNDING AND ISLAMIC SECURITIES: THE ROLE OF FINANCIAL LITERACY

This study investigates the effect of Islamic Financial Literacy (IFL) on the intention of prospective Muslim investors to invest through the Islamic securities crowdfunding FinTech (I-SCF FinTech) platform. Using data gathered from 100 respondents and employing the Partial Least Square – Structural Equation Modeling, we find IFL to have a significant effect on behavioral intention. The results of this study should benefit those involved in the I-SCF FinTech. Further, they point to the need to strengthen product and contract literacy and the importance of supervision and implementation of contracts that are in line with sharia principles through synergy between the Financial Service Authority (OJK) and the crowdfunding FinTech associations as well as relevant stakeholders.
Addressing challenges in gaining informed consent for a research study investigating falls in people with intellectual disability

Background People with intellectual disability encounter substantial health care discrepancies, yet are under-represented in research. Whilst people with intellectual disability can make valuable contributions to research and consequently improve their quality of life, researchers encounter multiple challenges including them in research. One challenge is to support them in making an informed decision to participate in research. Therefore the aim of this paper is to describe and reflect on a consent procedure used while gaining informed consent, when recruiting potential participants into an ongoing study. Methods A systematic and holistic consent procedure, underpinned by ethical guidelines, was developed and used alongside recommended strategies to engage people with intellectual disability in a research study. Results Only 3 participants (7.5%) were deemed capable of consenting independently, while 37 participants (92.5%) required the support of a proxy. Of these 37 participants, 22 participated in the consent process, while 15 depended mainly on their caregiver to make decisions for them. Adapted communication strategies were found to facilitate a person who has an intellectual disability’s participation in the consent procedure. The adapted written information sheets were of secondary importance. Conclusion The consent procedure was a respectful means of determining a person’s capacity to consent and indicating where there was a need for proxy consent. Appropriate communication strategies and the inclusion of familiar caregiver(s) were critical components Research participation 6 for facilitating the person with an intellectual disability to participate in the consent procedure.