Miracle-dz/UniFAR-FTUs huggingface dataset:
Smooth goodness-of-fit tests for composite hypothesis in hazard based models

Consider a counting process (N(t), t ∈ J) with compensator process (A(t), t ∈ J), where A(t) = ∫ 0 t Y(s)λ 0 (s)ds, [Y(t), t ∈ J} is an observable predictable process, and λ 0 (.) is an unknown hazard rate function. A general procedure for extending Neyman's smooth goodness-of-fit test for the composite null hypothesis H 0 : λ 0 (.) ∈ C = {λ 0 (.; η): η ∈ Γ ⊆ R q } is proposed and developed. The extension is obtained by embedding C in the class A k whose members are of the form λ 0 (.; η)exp(θ t ψ(.; η)), (η, θ) ∈ Γ x R k , where ψ(.; η) = (ψ 1 (.; η) ψ k (.; η)) t is a vector of observable random processes satisfying certain regularity conditions. The tests are based on quadratic forms of the statistic ∫ 0 T ψ(s; η) dM(s; η), where M(t; η) = N(t) - ∫ 0 t Y(s)λ 0 (s; η) ds and η is a restricted maximum likelihood estimator of η. Asymptotic properties of the test statistics are obtained under a sequence of local alternatives, and the asymptotic local powers of the tests are examined. The effect of estimating η by η is ascertained, and the problem of choosing the ψ-process is discussed. The procedure is illustrated by developing tests for testing that λ 0 (.) belongs to (i) the class of constant hazard rates and (ii) the class of Weibull hazard rates, with particular emphasis on the random censorship model. Simulation results concerning the achieved levels and powers of the tests are presented, and the procedures are applied to three data sets that have been considered in the literature.
Evaluation of score parameters for severity assessment of surgery and liver cirrhosis in rats

Severity assessment in animals is an ongoing field of research. In particular, the question of objectifiable and meaningful parameters of score-sheets, as well as their best combination, arise. This retrospective analysis investigates the suitability of a score-sheet for assessing severity and seeks to optimise it for predicting survival in 89 male Sprague Dawley rats (Rattus norvegicus), during an experiment evaluating the influence of liver cirrhosis by bile duct ligation (BDL) on vascular healing. The following five parameters were compared for their predictive power: (i) overall score; (ii) relative weight loss; (iii) general condition score; (iv) spontaneous behaviour score; and (v) the observer’s assessment whether pain might be present. Suitable cut-off values of these individual parameters and the combination of multiple parameters were investigated. A total of ten rats (11.2%; 10/89) died or had to be sacrificed at an early stage due to pre-defined humane endpoints. Neither the overall score nor any individual parameter yielded satisfactory results for predicting survival. Using retrospectively calculated cut-off values and combining the overall score with the observer’s assessment of whether the animal required analgesia (dipyrone) for pain relief resulted in an improved prediction of survival on the second post-operative day. This study demonstrates that combining score parameters was more suitable than using single ones and that experienced human judgement of animals can be useful in addition to objective parameters in the assessment of severity. By optimising the score-sheet and better understanding the burden of the model on rats, this study contributes to animal welfare.
Vector Partially Coherent Beams With Twisted Sinc-Correlation Structure and Their Statistical Properties

We define a new kind of radially polarized twisted sinc-correlation Schell-model (RPTSCSM) source and establish the source parameter conditions necessary to produce a physical beam. With the help of the extended Huygens-Fresnel integral, Several typical numerical examples are provided to study the influence of the source parameter and turbulent parameter on the statistical properties of such beams on propagation. It is shown that the intensity profiles of such beams always exhibit rotation and self-splitting on propagation, which is caused by the twisted phase of the beams. Moreover, the light intensity splits into an array and maintains its array distribution in free space. While the array gradually evolves to a hollow distribution with a dark core in a turbulence medium, indicating that the light beam may automatically restore the radial polarized light intensity distribution in atmospheric turbulence after a certain distance of propagation. Compared with the intensity, the impact of the twisted factor on the degree of polarization is to produce noticeable distortion around its distribution centre. When propagating in a turbulent atmosphere, the degree of polarization of such beams exhibits well-turbulent resistance. The degree of coherence would also experience self-splitting and rotation caused by the twisted factor, and a turbulent atmosphere has an important influence on the degree of coherence. Our results will benefit multi-particle manipulation and free-space optical communication.
Fractal Dimension of Rough Surface Estimated by the Cubic Covering Method

Aimed at overcoming the disadvantages in the triangular prism surface area method and the projective covering method, the cubic covering method for estimation of fractal dimension of rough surface is proposed. Moreover, the theoretical problem in the estimation of fractal dimension of rough surfaces is discussed. The comparison analysis shows that the results from the cubic covering method, as a real covering method from the view point of geometry, are closer to the actual value than the results estimated by the triangular prism surface area method and the projective covering method.
The roles they play: change in China’s climate leadership role during the post-Paris era

ABSTRACT China’s rise has accelerated expectations for it to step up as a climate leader – a role that has thus far been expected from developed countries. This article explores how China communicates its role to the international audience: is the role of global climate leader being increasingly seen as an appropriate one for China? From a role-theoretical perspective, it studies how China’s expectations changed during the post-Paris era 2016–2021. The article shows that China adapted its climate-leader role 2016–2020. However, a more apparent change in the role in 2021 exemplifies role learning. The article concludes that China has shifted the auxiliary role of climate leader to a more central position in its role set, reinforcing its master roles of responsible great power and leader of the developing world. Understanding China’s emerging leadership is crucial for recognizing the global variability of climate leadership conceptions, particularly in non-western contexts.
Beyond 5G Resource Slicing With Mixed-Numerologies for Mission Critical URLLC and eMBB Coexistence

Network slicing has been a significant technological advance in the 5G mobile network allowing delivery of diverse and demanding requirements. The slicing grants the ability to create customized virtual networks from the underlying physical network, while each virtual network can serve a different purpose. One of the main challenges yet is the allocation of resources to different slices, both to best serve different services and to use the resources in the most optimal way. In this paper, we study the radio resource slicing problem for Ultra-Reliable Low Latency Communications (URLLC) and enhanced Mobile Broadband (eMBB) as two prominent use cases. The URLLC and eMBB traffic is multiplexed over multiple numerologies in 5G New Radio, depending on their distinct service requirements. Therein, we present our optimization algorithm, Mixed-numerology Mini-slot based Resource Allocation (MiMRA), to minimize the impact on eMBB data rate due to puncturing by different URLLC traffic classes. Our strategy controls such impact by introducing a puncturing rate threshold. Further, we propose a scheduling mechanism that maximizes the sum rate of all eMBB users while maintaining the minimum data rate requirement of each eMBB user. The results obtained by simulation confirm the applicability of our proposed resource allocation algorithm.
Antecedents of Intention to Use E-Auction: An Empirical Study

Many public health organizations worldwide have used E-auctions to monitor, curtail, and improve the transmission of new coronavirus illnesses. However, user population size and acceptance of these technologies significantly impact their effectiveness. The current study’s goal was to determine what factors influence customers’ intent to use COVID-19 E-auctions by employing the Technology Acceptance Model (TAM) to the Jordanian setting. This study empirically assessed 310 Jordanian respondents using a quantitative approach known as Structural Equation Modeling (SEM). The research findings supported the majority of the proposed hypotheses, showing that behavioral intentions to use electronic bidding are highly influenced by perceived usability, perceived usefulness, trust in the government, social influence, and awareness. This research paper eventually contributes to the field of technology acceptance by developing a context-driven approach to the key pandemic components and features that influence different practices of technology acceptance.
Joint Use of Far‐Infrared and Mid‐Infrared Observation for Sounding Retrievals: Learning From the Past for Upcoming Far‐Infrared Missions

Atmosphere and surface properties are routinely retrieved from satellite measurements and extensively used in weather forecast and climate analysis. Satellite missions dedicated to fill the gap of far‐infrared (far‐IR) observations are scheduled to be launched this decade. To explore mid‐infrared (mid‐IR) and far‐IR joint retrievals for the future far‐IR satellite missions, this study uses an optimal‐estimation‐based method to retrieve atmospheric specific humidity and temperature profiles, surface skin temperature, and surface spectral emissivity from the Infrared Interferometer Sounder‐D (IRIS‐D) measurements in 1970, the only existing spaceborne far‐IR spectral observations with global coverage. Based on a set of criteria, two cases in the Arctic, which are most likely under clear‐sky conditions, are chosen for the retrieval experiments. Information content analysis suggests that the retrieved surface skin temperature and the mid‐IR surface spectral emissivity are highly sensitive to the true values while the retrieval estimates of far‐IR surface emissivity are subject to the variation of water vapor abundance. Results show that radiances based on the retrieved state variables are more consistent with the IRIS‐D observations compared to those based on the reanalysis data. Retrieval estimates of the state variables along with retrieval uncertainties generally fall within reasonable ranges. The relative uncertainties of retrieved state variables decrease compared to the a priori relative uncertainties. In addition, the necessity to retrieve surface emissivity is corroborated by a parallel retrieval experiment assuming a blackbody surface emissivity that has revealed significant distortions of retrieved specific humidity and temperature profiles in the Arctic lower troposphere.
Machine learning and molecular dynamics based models to predict the temperature dependent elastic properties of silver nanowires

Abstract Metallic nanowires are now extensively used in several nanoscale devices and applications. To further enhance their efficient usage, the estimation and prediction of thermal and mechanical properties of these nanowires is very important. Performing experimental studies on the objects of such a small dimension is quite challenging. Molecular dynamics simulation technique can easily simulate and perform virtual experimentation on the objects of nanoscale dimensions. In the present work, silver nanowires of known dimension simulated and a uniaxial stress has been implemented using the Molecular dynamics approach. The stress-strain data generated by MD simulation, has been utilized to train, test and validate different machine learning models. These machine-learning models offer a reasonably good amount of predictability of the tensile characteristics of the silver nanowire at any temperature.
FACTORS AFFECTING LIVELIHOOD STRATEGIES OF SMALLHOLDER TOBACCO AND NON-TOBACCO FARMERS AND OFF-FARM HOUSEHOLDS BENEFITTIN FROM LAND REFORM IN ZIMBABWE

The main objective of this paper was to determine the factors that affect the livelihood strategies of resettled smallholder farmers in Zimbabwe. The study was conducted in Manicaland Province in Zimbabwe, and the respondents were stratified into four groups. These were smallholder farmers resettled under the A1 and A2 models, as well as tobacco and non-tobacco smallholder farmers. The two models differ in how they were implemented and supported, which might lead to them having different livelihood strategies. A total of 300 respondents were surveyed, consisting of 114 tobacco and 149 non-tobacco farmers and 24 off-farm and 13 wageearner households in Manicaland province. The study used a Multinomial Logit model to investigate the factors influencing a household’s decision to choose different livelihood strategies. In the model, the dependent variables included four livelihood strategies, while the explanatory variables included various household social-economic and institutional factors. The results obtained from the multinomial logistic regression model established that gender and land size were significant at a level of 1%, and education, household size, access to credit and access to inputs were significant at 5% in the adoption of tobacco farming, access to credit and gender were significant at a 1% level in the adoption of non-tobacco farming, while education was significant at a 10% level in adopting off-farm were found to be significant in determining the adoption of the tobacco farming in the study area up to less than 10% probability level in adopting off-farm activities. Smallholder farmers who did not adopt tobacco farming indicated that limited land size, shortage of labour and access to tobacco inputs were the major impediments to adopting tobacco farming. The government should support the efforts of smallholder farmers to increase their livelihood strategies through unveiling credit lines for farming activities. Access to inputs for smallholder farmers should be made a priority by the government through the provision and fair distribution of adequate agricultural inputs.
QEPAS spectroscopy with fully tunable IC-ECDL with high bandwidth for the MIR range

To meet the requirements for multi-species gas analysis, Quartz-Enhanced Photo-Acoustic Spectroscopy (QEPAS) is used in combination with an IC-based External Cavity Laser system (IC-ECL). The laser system allows the coverage of a wavelength range of 285 nm with an output power of several mW. By integrating piezoelectric actuators as well as resonantly driven MEMS actuators, extremely high sampling rates can be achieved. In this work, results on the detection of multiple trace gases by sequential quasi-simultaneous measurements are presented. The requirements of multi-species detection, output power, tuning range and detection rate are met by our work.
A tutorial on the precessional behaviour of hydrogen nuclei in external magnetic fields

The purpose of this tutorial is to derive the precessional characteristics of the magnetic moments of hydrogen nuclei in the presence of a constant external magnetic field using the Dirac bra-ket formulation of quantum mechanics (QM). This behaviour has many applications, most notably in nuclear magnetic resonance (NMR) and magnetic resonance (MR) imaging. Many NMR and MR imaging textbooks claim that the QM expectation value of the magnetic moment of a proton in a magnetic field reduces to the classical picture of a precessing magnetic dipole. This paper validates this con- clusion by reducing the cumbersome QM integrals using Dirac notation and matrix algebra, and then comparing this result with the classical picture. It illustrates the connections between the quantum and classical pictures and demonstrates quan- titatively how they differ and how they are similar. This tutorial targets students and researchers interested in the funda- mental physics behind the MR phenomenon and assumes that the reader has a basic understanding of QM. This may be helpful for undergraduate QM students learning about spin angular momentum and Dirac notation.
Identifying obstacles encountered at different stages of the disaster management cycle (DMC) and its implications for rural flooding in Pakistan

The world has seen a number of natural hazards, but among them, floods are perhaps the most frequent devastating natural hazard, resulting in more human causalities and financial losses. Rural inundation has become an issue of concern in various parts of the world, including Pakistan. Over the past few decades, it has been hard for local institutions and rural populations to recover from the trauma inflicted by these events. The disaster risk management cycle is a well-known tool for coping with disasters and their consequences. Yet, the DRM cycle efficacy has been questioned in various rural settings. Thus, this paper applied a programmatic strategy to understand the challenges disaster management authorities and communities face in managing flood risks through the conventional disaster management cycle in Khyber Pakhtunkhwa province, Pakistan. The study objective was accomplished by using both qualitative and exploratory research designs. Four communities (namely, Peshawar, Charsadda, Nowshera, and Dera Ismail Khan) with a historical record of flooding were chosen for focus group discussion (32 in total) using a purposive sampling method. Additionally, 31 key informant interviews were undertaken from pertinent local disaster risk management institutions. We employed a thematic analysis to classify responses and obstacles into the various stages of the disaster management cycle. The findings of this study from interviews and focus groups provided some new insight into the conventional DRM cycle. The issues and challenges encountered by institutions and the community members were divided into four stages: 1-mitigation, 2-preparedness, 3-rescue and relief (R&R), and 4-rehabilitation and recovery (R&R). Based on the findings, it seems that local disaster management institutions still rely on reactive strategies and deal with flood hazards on an ad hoc basis. Poor governance and a lack of responses for present development trajectories were also highlighted as reasons why flood risk management is still challenging. There is an urgent need to perform susceptibility and risk assessments for multiple hazards and develop specialized plans that follow disaster risk reduction principles and adaptation to climate change. This study recommends incorporating resilience and adaptation to climate change into the current disaster management cycle to prevent or reduce future hazards and risks in rural areas.
Nutritional diagnosis of ‘Montenegrina’ mandarin orchards at the southern Brazil

The correct nutrition of orchards from fertilizer management directly influences fruit yield. Therefore, the objective was to evaluate the nutritional status of orchards of the ‘Montenegrina’ mandarin ( Citrus deliciosa Tenore) grafted on Poncirus trifoliata Raf. in southern Brazil. The study included analyzes of soil and leaf tissue from 58 commercial orchards. More than 60% of the orchards were diagnosed with K and Mg insufficiency and more than 30% had an excess of N. There was an insufficiency in Mn and Zn of 60 and 96%, respectively, despite the levels of these micronutrients in the soil being high in both depths studied. In addition, no significant correlations were observed between the contents of a given nutrient in the soil and in the leaves, except for the Ca/Mg ratio. Insufficiency was observed in the leaf contents of K, Mg, Mn and Zn and excesses of N and Cu in the orchards. The use of phosphate and potassium fertilizers requires adjustments due to the excessive content of these nutrients in the soil. Pre-planting acidity correction and soil acidity management in ‘Montenegrina’ mandarin orchards already implanted needs to be optimized.
Placebo hypoalgesic and nocebo hyperalgesic effects in post-extraction patients—A cross sectional study

Background and objectives Pain is an unpleasant sensory and emotional experience that affects people’s physical, mental, and social health. Patients at times present with postoperative pain with no clinical signs after the surgical dental procedures and adequate pharmacological management. This can be due to the amplified emotional component of the individual in their postoperative period. Hence, this study aimed to estimate the association between placebo, nocebo effects, and postoperative pain associated with tooth extraction procedures. Methods A cross-sectional study was conducted among 301 patients attending the Department of Oral and Maxillofacial Surgery for tooth extraction. Preoperatively, the expected postoperative pain score was recorded using the “Numerical Rating Scale” (NRS), Anxiety and Depression were assessed using the “Hospital Anxiety and Depression Scale” (HADS), and Patients’ expectancy regarding the treatment outcome was assessed using the “Credibility Expectancy Questionnaire” (CEQ). Observed postoperative pain scores at the 6th hour, 24th hour, and peak pain score of the day were recorded using the NRS. Results There were statistically significant associations (p < 0.05) found between expected and observed postoperative pain, preoperative anxiety and observed postoperative pain, preoperative depression and observed postoperative pain, placebo, nocebo effects, and observed postoperative pain. Interpretation and conclusion Our study showed a strong association between these variables suggesting that post-extraction pain is a multifaceted condition wherein pain expectation, preoperative anxiety, depression, and expectancy regarding the treatment outcome should be scrutinized before the extraction procedure.
Homology analysis of malicious code and family clustering

With the problem of the explosive growth of malicious code and many of the malicious samples are variations of previously encountered samples, this paper presents a novel approach to investigate the homology of malicious code based on behavior characteristics. To distinguish the variations of malicious code, it studies the malicious behavior of malwares,then computes the similarity of characteristics and the call graphs which are extracted by disassembly tools. It employs the clustering algorithms of DBSCAN to discover the family of malicious code. Experiments show that it effectively investigates the homology of malicious code and cluster variations into different malicious code family.