Miracle-dz/UniFAR-FTUs huggingface dataset:
Voluntary Direct Method Cash Flow Disclosure in the U . S . : Determinants and Incremental Usefulness

This study explores the determinants and incremental usefulness of the direct method operating cash flow (CFO) disclosures in a voluntary setting (the U.S.). The net benefits of disclosure choice come into sharp focus in such a setting, permitting a direct study of the attributes of firms most likely to benefit from such disclosures. We first investigate firm-level attributes or economic settings associated with voluntarily adopting firms. Second, we study whether the disclosed components of CFO in this voluntary setting, are incrementally useful beyond the estimated analogues in predicting future CFO and earnings. We further explore whether any incremental usefulness of the disclosed components varies under the different firm level or economic settings identified in the first stage. Our results show that firms are more likely to adopt the direct method when they have higher leverage, lower discretionary accruals, longer operating cycles, less complex business operations, and when they operate in a less competitive market. In addition, we find that the disclosed direct method components of CFO are incrementally more useful in the following settings where firms have higher incentives to adopt the DM: more volatile life cycle stages, large estimation differences, higher reliance on debt financing, and longer operating cycles. Baljit K. Sidhu Chuan Yu
Linking Menopausal Status , Climacteric and Psychological Symptoms : Evidence from Middle Aged Pakistani Women

Menopause is a crucial and normal developmental phase in a life of woman. During this period, women experience social, psychological and physical changes. Menopausal symptoms experienced by women may differ enormously from culture to culture; consequently, there is a need to examine these signs and linked to risk factors in different population. This current paper designed to investigate the relationship between attitude towards menopause and climacteric and psychological symptoms of Pakistani women in menopause. Moreover, this study also investigated the differences in psychological and climacteric symptoms among postmenopausal premenopausal and perimenopausal women. Purposive sampling technique was used based on cross-sectional design. One hundred fifty participants (premenopausal, n = 57; perimenopausal, n = 33; postmenopausal, n=60) were included from different private and government hospitals of Peshawar, Islamabad and Rawalpindi, Pakistan from 2015 to 2016. Age ranged from 40 to 60 years. Two scales, Greene Climacteric Scale (Salik, & Kamal, 2010) and depression, anxiety and stress scale (Lovibond & Lovibond, 1995; Zafar & Khalily, 2015) were used to measure psychological, physical, vasomotor sexual Dysfunction, stress, anxiety and depression. This current paper results demonstrated that postmenopausal women tended to have somatic, sexual dysfunction and psychological symptoms as compared to premenopausal, perimenopausal women. This study would be helpful to understand health and psychological problems of menopausal women
Open top chamber microclimate may limit photosynthetic processes in Antarctic lichen: Case study from King George Island, Antarctica

Long-term manipulated warming experiments using the open top chamber (OTC) approach tend to mimick the future climate and predict the changes in photosynthesis and production of vegetation under globally changed climate. In Antarctica, several long-term experiments are carried out recently. Here we report to the lichens grown in OTCs installed at the Fildes Peninsula (King George Island). The field study compares primary photochemical processes of photosynthesis in Antarctic lichen Placopsis antarctica grown for one year in OTC and compared to outside plot (control). We measured effective quantum yield of photosystem II (ΦPSII) of green algae part of thallus in 10 min. interval for 12 days. We examined the responses of diurnal ΦPSII to PAR in relation to environmental factors through continuous 12-d-long monitoring of chlorophyll fluorescence parameters ΦPSII in particular. Daily courses of ΦPSII and photosynthetic electron transport rate (ETR) to photosynthetically active radiation (PAR) and hydration state of thallus have been assumed to reflect changes in physiological status of P. antarctica in changing Antarctic environment. The data indicate that OTC microenvironment may lead to partial limitation of photosynthetic processes in P. antarctica during austral summer season. The limitation is caused by accelerated dehydration of thallus in OTC compared to the outside generally colder control plot, and thus shortened physiologically active period of lichens in OTC.
Acquisition of Probabilistic Behavior Decision Model based on the Interactive Teaching Method

In this paper, we propose a novel method for mobile robots to acquire new autonomous behaviors gradually based on interaction between human and robots. In this method, behavior decision models are constructed using statistical process for experiences of interaction and teaching, and the robot expresses sureness of its own decision using stochastic reasoning. The robot not only decides behavior using the sureness, but also makes suggestions and questions for the user using the sureness. Consequently, the sureness enables the behavior acquisition to be more e ective. We refer to this kind of method as \Interactive Teaching" method. We investigate the feasibility of this method for obstacle avoidance tasks with mobile robots. Through experiments at both virtual and real mobile robot, we have con rmed that the mobile robot acquires robust behavior decision models against changes of environment and uncertainties of sensors, through only several teaching.
Phytomass of lettuce cultivars under water replenishment levels.

Water scarcity in the semi-arid region causes significant losses in the socioeconomic activities, with reduction in agriculture. Therefore, this study aimed to evaluate the effect of the application of irrigation depths on the phytomass accumulation of lettuce cultivars. The experiment was carried out at the Academic Unit of Agricultural Engineering, in 10 beds composed of 78 plants each, at spacing of 0.25 × 0.30 m. The treatments were set in a 5 x 3 factorial scheme, with five water replacement levels, The irrigation depths were applied based on the reference evapotranspiration – ETo, as follows: 70% (L1), 80% (L2), 90% (L3), 100% (L4) and 115% (L5) of the reference evapotranspiration – ETo, and three cultivars: Elba’ – C1, ‘Iceberg’ – C2 and ‘Looseleaf’ – C3, four replicates. Irrigations were applied through a drip system with the aid of the program ETo calculator-FAO Penman-Monteith to estimate the reference evapotranspiration. The following variables were determined: fresh matter (FM), dry matter (DM), root fresh matter (RFM), root dry matter (RDM), number of leaves (NL) and plant height (PH). According to the results, the increment in irrigation depths increased leaf fresh matter, number of leaves, plant height and root dry matter. The irrigation depth of 192.4 mm cycle -1 , i.e., 100% of evapotranspiration under field conditions led to greater yield.
THE INFLUENCE OF TOPOGRAPHY CHARACTERISTICS ON THE NUMERICAL WEATHER FORECAST WITH THE WRF MODEL IN CASES OF SEVERE WEATHER

The aim of this study is investigating the influence of topography data over Romanian territory on the numerical weather forecast of the WRF (Weather Research and Forecasting) model in cases of severe weather events. The WRF model was run for two different weather events: 17 July 2011 and 3 February 2012. In both cases, heavy precipitation and strong wind were registered on Romanian territory. Topography data were used at three horizontal resolutions: 2 minutes, 30 seconds and 3 seconds. The use of the topography data at these resolutions resulted in differences between the numerical weather forecasts of the WRF model.
OPTIMAL CONTROL POLICIES FOR AN M/M/1 QUEUE WITH A REMOVABLE SERVER AND DYNAMIC SERVICE RATES

Abstract We consider an M/M/1 queue with a removable server that dynamically chooses its service rate from a set of finitely many rates. If the server is off, the system must warm up for a random, exponentially distributed amount of time, before it can begin processing jobs. We show under the average cost criterion, that work conserving policies are optimal. We then demonstrate the optimal policy can be characterized by a threshold for turning on the server and the optimal service rate increases monotonically with the number in system. Finally, we present some numerical experiments to provide insights into the practicality of having both a removable server and service rate control.
COMPARATIVE STUDY OF ‘ BOD ’ , ‘ DO ’ AND pH OF DISTILLERY TREATED AND UNTREATED WASTE WATER

Industrial processes create a variety of wastewater pollutants; which are difficult and costly to treat. The present study is under taken to assess the level of physiochemical parameters of the distillery spent wash. These parameters will compare with Bureau of Indian Standards. Untreated effluent is found to have high contents of BOD, and low contents of DO. According to the permissible limit suggested the Bureau of Indian Standards the untreated effluents is toxic to plant so it is not permissible for irrigation. The results reflect that the treated effluents are not highly polluted and they satisfy the Bureau of Indian Standards values and therefore can be used for irrigation purposes.It is one of the most complex, and strongest organic industrial effluent, having extremely high BOD values. Because of the high concentration of organic load. The paper reviews the status of BOD, DO and pH values before and after treatment of the distillery wastewater.
Climate variability modes and their impact on the hydrological cycle-A model evaluation study

Climate models are essential tools for studying and projecting climate change and climate variability. A thorough assessment of a model’s ability to reproduce the observed present-day climate is therefore a crucial prerequisite for building up confidence in the model’s ability to project the future climate. This includes modes of natural climate variability such as the El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) that are spontaneously generated and that need not exhibit the same chronological sequence in models as in nature. The main focus of this thesis is an assessment of representation of ENSO and PDO as well as the impact of these climate modes on cloud parameters and precipitation. For this, different simulations from the Max Planck Institute Earth System Model (MPI-ESM) and the ECHAM/MESSy Atmospheric Chemistry Model (EMAC) are evaluated. These include a coupled fully coupled ocean atmosphere simulation from the MPI-ESM, a simulation with prescribed SSTs from both MPI-ESM and EMAC, and an EMAC simulation which is nudged towards realistic meteorology. To evaluate the model simulations, a variety of different observational data sets are used. To evaluate the climate modes, the National Center for Atmospheric Research (NCAR) Climate Variability Diagnostics Package (CVDP) has been implemented into the Earth System Model Evaluation Tool (ESMValTool) as part of this thesis. The CVDP computes statistical key metrics of internal climate variability for model simulations and observational data sets. The ESMValTool is a software tool developed by multiple institutions that aims at improving routine Earth System Models (ESM) evaluation. Additionally, new diagnostics have been integrated into the ESMValTool to evaluate the response of clouds and precipitation to the selected modes of climate variability ENSO and PDO. The results show that the spatial structure of the PDO simulated by the MPI-ESM coupled is quite realistic and in terms of temporal variability, the MPI-ESM coupled produces a periodic response of approximately the same frequency as observed – that is, periods of 3 – 7 years for ENSO, and ~20 years for the PDO. However, the MPI-ESM coupled model only weakly resembles the observed asymmetry between the El Niño and La Niña events, but simulates a quite realistic SST evolution to ENSO. Teleconnections of the atmospheric circulation with ENSO including corresponding changes in temperature, precipitation, and cloud properties are reasonably well captured by the MPI-ESM and EMAC model simulations. Systematic differences in the performance of the coupled and the atmosphere-only model runs with MPI-ESM and between the free-running and the nudged EMAC model simulations in reproducing the observed relationships between PDO, ENSO, and local SST changes and cloud parameters and precipitation are rather small. This points to the necessity to improve model parameterizations of the relevant physical processes such as convection or boundary layer processes. Content
Dependency tracking in real-time fault-tolerant systems

During the development and maintenance of a large real-time system, it is difficult to fully understand system semantics and maintain system consistency due to complex system semantic dependencies. Logical semantics, timing, and shared resources constitute the three principle dimensions of semantic dependencies. Semantic dependencies introduce hidden side-effects into the system because they are often not explicitly documented in the source code. When the system consists of multiple configurations, these side-effects become much more obscure and inconsistent configurations at runtime are likely. Certain fault recovery mechanisms and domain-specific applications can introduce such multi-configuration systems. When making a change to the system, the scope of change is too complex to be handled without automation, since the far-reaching effects are beyond local component interactions. Existing design and development frameworks are not capable of capturing such complex multi-dimensional dependencies. In particular, in order to capture logical semantics and time-sensitive logical semantics in real-time systems, novel modeling notations are necessary. Current modeling techniques cannot discover hidden side-effects, identify inconsistent configurations, and estimate the impact of a change. We have developed an Architectural Description Language (ADL) that enables system developers and maintainers to capture and record hidden system dependencies incrementally. A restricted application domain involving real-time closed-loop guidance and control is to demonstrate how logical semantics are captured to create an architectural model. Implemented in a CASE tool environment, the static analyses based on the architectural model provide assistance to understand hidden side-effects, and change impact. Furthermore, a set of configuration constraints can be automatically derived from the architectural model based on the configuration inconsistencies identified through the analyses. The identified model inconsistencies can be avoided by having the run-time system monitor the associated system states and enforce the derived configuration constraints.
Offi cial Organ of the European Association of Psychological Assessment european journal of psychological assessment

The VIA Classification of Character Strengths and Virtues (Peterson & Seligman, 2004) has been an influential contribution to the study of prosocial traits, and provided the basis for the VIA Inventory of Strengths (VIA-IS). Inherent to the Classification is the assumption that the character strengths included in the model are cross-culturally relevant. The emergence of a latent trait model for the VIA Classification from exploratory factor analytic research and the availability of data from translated versions of the VIA-IS provides a basis for evaluating this assumption. A sample of 15,540 individuals from 16 nations who completed the VIA-IS online was used to evaluate measurement equivalence. Multigroup confirmatory factor analysis and a relatively new statistical procedure, alignment analysis, were used to evaluate configural, metric, and scalar invariance across translations of the instrument. Consistent support was found for configural and metric invariance, and scalar invariance was also demonstrated under a number of circumstances. The findings lend support to the cross-cultural relevance of the VIA Classification of Character Strengths and Virtues as well as to existing translations of the VIA-IS.
RUSSIAN WORD SENSE INDUCTION BY CLUSTERING AVERAGED

The paper reports our participation in the shared task on word sense induction and disambiguation for the Russian language (RUSSE’2018). Our team was ranked 2nd for the wiki-wiki dataset (containing mostly homonyms) and 3rd for the bts-rnc and active-dict datasets (containing mostly polysemous words) among all 19 participants. The method we employed was extremely naive. It implied representing contexts of ambiguous words as averaged word embedding vectors, using off-the-shelf pre-trained distributional models. Then, these vector representations were clustered with mainstream clustering techniques, thus producing the groups corresponding to the ambiguous word’ senses. As a side result, we show that word embedding models trained on small but balanced corpora can be superior to those trained on large but noisy data—not only in intrinsic evaluation, but also in downstream tasks like word sense induction.
SHEAR STRENGTH OF DRY KEYED JOINTS AND COMPARISON WITH DIFFERENT FORMULATIONS

The shear strength of multiple-keyed joints is a very important part of the design of prestressed segmental concrete structures. This type of structures is widely used but the formulations of different design codes deal to different values of the shear strength of joints. In this paper, it has been developed a finite element model of four different types of joints, with a number of keys varying between one and seven. The brittle cracking model was used for the material. The material model has been calibrated and validated using the P-δ curve from single edge notched beams subjected to three-point-bending test. The model has been tested comparing the predicted response with the experimental results for one and three keys. Then, it has been analysed the behaviour of joints and their dependence on the number of keys. The results have been compared with the formulation of different codes and authors. The results show that the average shear stress transferred across the dry keyed joints decreases with the number of keys but this effect is less appreciated as the compression stress acting on the joint increases. Comparing with the formulas of design codes, the ATEP formula underestimates the shear capacity of the joints, and AASHTO formula overestimates it in the case of multiple keys and low prestressing force.
RESEARCH ON FAILURE SIMULATION OF CIVIL AIRCRAFT FLIGHT MANAGEMENT SYSTEM

It is focused upon the research on the civil aircraft failure simulation integrated with Flight management system (FMS). The research includes the failures embedded in the system based FMS’s control and management, failure responses, and their exercising influence upon other subsystems. The different response characteristics and failure tolerance levels under multi-failure modalities of FMS are checked through simulation tests by setting different multi-failure modalities. The responses to embedded failures about subsystems referred to FMS in civil aircraft are testified and verified, and the flight performances and safety qualities of civil aircraft integrated with FMS are evaluated. So the failure simulation flight test technology with FMS in accordance with airworthiness is testified and could be applied to authoritative flight tests for a new type airplane.
Deep Learning for Error Prediction In MIMO-OFDM system With Maximum Likelihood Detector

To increase link throughput in multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, transmission parameters such as code rate and modulation order are required to be set adaptively. Therefore, block error rate (BLER) becomes a crucial measure which illustrates the quality of the link, thus being used in Link Adaptation (LA) to determine the transmission parameters. However, existing methods to predict BLER are only valid for linear detectors, e.g. Minimum Mean Square Error (MMSE) detector [1]. In this thesis, we show that signal-to-interference-plus-noise ratio (SINR) exists in MIMO-OFDM system with MLD (maximum likelihood detection). Then, a machine learning based method with Deep Neural Network (DNN) is proposed to analyze the relation between input features (channel matrix, modulation and coding scheme (MCS), signal-to-noise ratio(SNR)) and labels (CRC). Results shows that the classification of DNN is good. However, there is still deviation when compared output of DNN with the simulated BLER.
Some New Types of Open and Closed Sets in Minimal Structures-II

In this article different forms of closed sets in m-spaces are introduced, studied and characterized. We show that the obtained results are a generalization of many of the results obtained by N. Rajesh in [10] and N. Rajesh et al. in [11]. Mathematics Subject Classification: 54A05, 54A20, 54C08, 54D10
Noise-robust 1200-bps voice coding

A novel voice coding algorithm for tactical systems such as Minterm has been developed. The Soft Voicing Vocoder (SVV) algorithm meets three requirements for tactical systems: (1) low bit rate (2400 bps and below); (2) high intelligibility despite acoustic background noise; and (3) modest complexity. At 1200 bps, SVV gives higher intelligibility in noise than the standard LPC-10 2400 bps voice algorithm as defined in Fed. Std. 1015. Intelligibility improves even further when the SVV bit rate is increased to 2400 bps. The SVV is less than double the complexity of the standard 2400 bps algorithm, and can be implemented in real time on a single-chip DSP (digital signal processor) such as the TI TMS320C50. The author describes the algorithm and summarizes the performance. Finally, he shows the current implementation status and areas for further work. <<ETX>>
Sustainability assessment in supply chains-A literature review of sustainability aspects and the development of indicators Presenting :

Sustainable Supply Chain Management (SSCM) is of growing interest nowadays as the complexity of global supply chains and the shift of competition from inter-firm to intersupply chain level are increasing, and companies are motivated by cost-reduction possibilities and consumers’ pressure. Original Equipment Manufacturers (OEMs) already internalized to some extent the sustainability trend but the management of sustainability in the whole supply chain remains challenging. In order to fill the research gap we identified sustainability performance measurement of supply chains in the automotive and electronic industry-, we conducted a literature analysis and interviews with experts from industries, interest groups and NGOs. Our purpose is to review the existing literature on sustainable supply chain management and sustainability assessment and measurement on business and SC level. We aim at highlighting relevant sustainability aspects to gather and develop corresponding indicators for industries. Many articles focus on sustainability, especially on the economic and environmental dimensions, but few documents refer to the three dimensions of sustainability together. In addition, sustainability in the supply chain focuses on environmental, regulatory and economic issues but not often on the social dimension. Research on social sustainability is poor although it is a core issue in today ́s society, where respect for Human Rights and working hours are often pointed out. Finally, no complete and comprehensive set of sustainability indicators for supply chains exist so far. Our literature review and further work is meant to gather the most precise and complete information to make it available to all stakeholders concerned, particularly companies from the automotive and electronics sectors.