Miracle-dz/UniFAR-FTUs huggingface dataset:
An introduction to the distribution of carbon stocks in temperate broadleaf forests of northern Iran

Northern forests of Iran are among the most important plant communities in Iran due to their dynamic and diverse vegetation composition and fertile soils. There is little information about carbon stocks of these forests. In the present study, aboveand belowground carbon stocks of trees, litter, herbs and soil organic carbon stock at three selected sites of these forests were calculated using random plots and non-destructive sampling. The FAO method was used for carbon estimation of trees and Walkley-Black method was used for soil carbon stock and carbon coefficient was estimated directly. The results showed that both the tree carbon stocks and soil carbon stocks increased from east to west with increasing altitude, showing significant differences. The results also indicate that these forests have a high carbon sequestration potential as a green belt across the northern slopes of the Alborz Mountains, when the contribution of the aboveground section was greater than that of the belowground section (soil and roots) at all sites.
Digitizing Disclosure: The Case of Restaurant Hygiene Grades

Restaurant hygiene grades have become a success story of public disclosure of government inspections. Yet in most cities, hygiene grades go unnoticed on government websites with no standardized format across cities. This paper reports on the preliminary results of an initiative aimed at digitizing hygiene grades. The goal of the initiative is to increase awareness of hygiene by leveraging digital platforms where consumers are already looking for restaurant information. Working with the San Francisco Department of Public Health and the restaurant review website Yelp.com, we matched hygiene results to Yelp data and published all matched records onto Yelp. This paper documents the process and reports the initial results from San Francisco. The initial results show that there is a strong correlation between Yelp ratings and hygiene grades. However, thus far, there is little customer response to the hygiene grades. Restaurants with low grades do not experience a drop in their Yelp ratings or number of reviews in the treatment period. Ongoing experiments are aimed at better understanding mechanisms behind this lack of response.
THE INTERACTIVE MODIFICATION OF GRIDDED FORECASTS

Since 1985, the Techniques Development Laboratory (TDL) has been building and evaluat ing techniques w hich enable the forecaster to interact ively prepare digital forecasts of w eather elements. These techniques are being developed to test concepts and to gain experience in preparat ion for the Advanced Weather Interact ive Processing System (AWIPS) scheduled for deployment by the National Weather Service start ing in 1996.
Employees' attitudes towards innovation in workplace: an examination of the impacts of new technology on multinational corporations (MNCs)

Most scholars hold the view that organisations cannot survive in the ever changing and turbulent environment in which they operate without human resource. The reason being that employees’ attitudes can have adverse effects on the achievement and the realisation of the strategic goals of MNCs and eventual failure of its mission when a new technology is introduced without proper cognisance of the attitudes of employees to innovation. Against this background, this article adopts the tricomponent theory of attitudes and Technology Acceptance Model (TAM) to explain employees’ attitudes towards innovation in workplace, and examines the impact of new technology on MNCs. Consequently, the article recommends among others, green-HRM management processes.
Cell for electrochemical and electrophysiological measurements in peripheral nerves

The aim of the work was to develop the cell to be used in electrochemical and electrophysiological measurements in peripheral nerves, when electrical stimulating pulses are selectively applied to preselected locations along the nerve. The main part of the cell is the silicone spiral cuff system, including spiral matrix of ninety-nine platinum electrodes, arranged in eleven longitudinal spiral electrode configurations of nine electrodes for establishing electrical contact with specific sites on the peripheral nerve. To maximize the fatigue life of lead wires connected to the electrodes, which should sustain frequent bending, a high frequency miniature and highly flexible, multi-stranded and enameled copper wire, was used. The cell is made of Plexiglas and is instrumented with the precision temperature probe, Ag/AgCl reference electrode, 3D micro-manipulator positioning system and custom designed force transducers to measure stretching and radial pressure that could be applied on nerve segment during measurements. Izvleček: Namen dela je bil razviti celico za izvajanje elektrokemijskih in elektrofizioloških meritev na perifernih živcih v času selektivnega dovajanja stimulacijskih impulzov na predhodno izbrana mesta 40 pečlin, p., RiBaRič, s. , RoZman, j. RMZ-M&G 2011, 58 IntroductIon One of the greatest problems in nonselective vagus nerve stimulation used worldwide as a potentially useful therapy for treating various heart conditions and certain types of intractable epilepsy and major depression is nonselective stimulation of particular superficial regions as well as non-selective stimulation of fibers innervating a targeting organ. [1, 2, 3, 4, 5, 6] The result is the occurrence of undesirable side effects such as: an intermittent decrease in respiratory flow during sleep, disordered breathing, loud snoring, obstructive sleep aponea, alteration of voice, coughing, pharyngitis, throat pain, hoarseness, frank laryngeal musvzdolž živca. Najpomembnejši del celice je spiralna silikonska objemka, ki vključuje spiralno matriko devetindevedesetih elektrod, razporejenih v enajst longitudinalnih skupin po devet elektrod za vzpostavitev stika s posameznimi mesti na perifernem živcu. Za čim daljšo trajnostno dobo žic, povezanih z elektrodami, ki morajo vzdržati pogosto upogibanje, je bila izbrana visokofrekvenčna, drobna in zelo upogljiva ter lakirana bakrena pletenica. Sama celica je izdelana iz pleksi stekla in opremljena s precizijsko temperaturno sondo, referenčno elektrodo Ag/AgCl, z mikromanipulatorjem za 3D pozicioniranje in s posebej izdelanimi senzorji sile za merjenje natega in radialnega tlaka, ki mu bo med meritvami izpostavljen vzorec živca.
Econometric analysis of the effects of aggregate expenditure on job growth in the private sector: the South African case

The private sector contributes to job creation either directly by creating new positions for job seekers or indirectly by increasing growth that results in job creation for unemployed people. This study employed an Autoregressive Distributed Lag (ARDL) model to analyse the long and short run effects of aggregate expenditure on job creation in the private sector in South Africa. The findings indicated that there is a long run relationship between aggregate expenditure and job creation in the private sector. Investment spending and net exports are the aggregate expenditure components that create long-term jobs, whereas consumer consumption and government spending lead to possible long run job destruction. The Error Correction Model (ECM) results revealed that consumption and investment spending create jobs in the short run, while the Granger-causality test suggested that a bidirectional causal relationship exists between consumption, investment spending and employment in the private sector. The study concluded that the negative effect of consumption on private employment might be due to the consumption of imported goods and services. Thus, the employment situation in South Africa could be improved if more focus is placed on consumption of domestic products.
A Review System Based On Product Features In A Mobile A Review System Based On Product Features In A Mobile Environment Environment

With the rapid growth of the mobile commerce, firms have been trying to get their online channels optimized for the mobile devices. However, many contents on online shopping sites are still focused on a desktop PC environment. Especially, consumer reviews are difficult to browse and grasp via a mobile device. Usually, it is not helpful to simply reduce the size of fonts or photos to fit to mobile devices without a fundamental transformation of the review presentation. In this study, we suggest a feature-based summarization process of consumer reviews in mobile environment. Further, we illustrate an implementation of the process by applying opinion mining techniques to product reviews crawled from a major shopping site in Korean. Finally, a plan for a controlled laboratory experiment is proposed to validate the effectiveness of the suggested review framework in this study
Statistical Mechanics: Lecture 9 –

Quantum Statistical Mechanics Postulates of Quantum Statistical Mechanics Till now whatever we studied in statistical mechanics, was by using classical laws of motion. However, all systems in nature follow quantum mechanics, which is the more fundamental theory. In many situations it is a good approximation to describe even microscopic particles classically. For example, large molecules and colloid particles can be described well using classical laws, and hence using classical statistical mechanics suffices. However, majority of systems which we want to describe using statistical mechanics, are inherently quantum in nature, and classical laws cannot be used to describe them. For example, a gas of free electrons should be described using quantum mechanics as things like Pauli’s exclusion principle are important for them. In the following we will formulate statistical mechanics for quantum systems. The state of a quantum system can be described at any instant of time by its wave function Ψ. In a particular representation, Ψ will be a function of position coordinates of all the particles, and time. In another representation, it will be a function of momenta of all the particles, and time. In general it can be just be represented as a vector in Hilbert space, |Ψ〉. |Ψ〉 can also be written as a linear combination of eigenfunctions of any Hermitian operator of the Hilbert space. We will write it in terms of the eigenstates of the Hamiltonian of the system Ĥ, the so-called energy eigenstates, given by Ĥ |Φn〉 En |Φn〉. The state of the system can now be written as
Structural and Genetic Analyses of the Mycobacterium tuberculosis Protein Kinase B Sensor Domain Identify a Potential Ligand Binding Site

Monitoring the environment with serine/threonine protein kinases is critical for growth and survival of Mycobacterium tuberculosis , a devastating human pathogen. Protein Kinase B (PknB) is a trans-membrane serine/threonine protein kinase that acts as an essential regulator of mycobacterial growth and division. The PknB extracellular domain (ECD) consists of four repeats homologous to penicillin-binding protein and serine/threonine kinase associated (PASTA) domains, and binds fragments of peptidoglycan. These properties suggest that PknB activity is modulated by ECD binding to peptidoglycan substructures, however the molecular mechanisms underpinning PknB regulation remain unclear. In this study, we report structural and genetic characterization of the PknB ECD. We determined the crystal structures of overlapping ECD fragments at near atomic resolution, built a model of the full ECD, and discovered a region on the C-terminal PASTA domain that has the properties of a ligand-binding site. Hydrophobic interaction between this surface and a bound molecule of citrate was observed in a crystal structure. Our genetic analyses in Mycobacterium tuberculosis showed that nonfunctional alleles were produced either by deletion of any of single PASTA domain or by mutation of individual conserved residues lining the putative ligand-binding surface of the C-terminal PASTA repeat. These results define two distinct structural features necessary for PknB signal transduction, a fully extended ECD and a conserved, membrane-distal putative ligand-binding site.
P o S ( L H C P 2 0 1 9 ) 0 9 3 Open and hidden heavy-flavor production and flow in Heavy Ion Collisions

Their fast formation and microscopic scale of heavy flavor (HF) probes are ideal for a QuarkGluon Plasma (QGP) tomography. Besides, the large fraction of energy carried by the measured heavy flavor hadron from the hard process fragmentation also favors a precise study of the partonic density and initial state effects in nucleus. LHC experiments are exploring heavy flavor probes in different manners such as the study of partonic energy loss in cold and QGP medium, diffusion properties, hadron coalescence and local free energy quantification using bound state quarkonia. This manuscript summarizes the most recent experimental developments in the field coming from all LHC experiments using data taken in pPb and PbPb collisions in collision energies ranging from 86.6 GeV to 8.16 TeV.
Segmenting Taipei’s Real Estate Data – A Cluster Analysis

Data mining has been widely used for knowledge discovery from large amount of data. In this paper, clustering analysis is applied to Taiwan government open data platform (DATA.GOV.TW), segmenting the real estate data so as to understand the real estate market structure in Taiwan. This paper use design science research methodology (DSRM) as research method. The result provides valuable insights into market structures in Taipei City that has limited addressed in past research and contributes to real estate agencies and practitioners an insight-seeking approach that they can follow to generate values from data.
Combination of Evolutionary Algorithms and Constraint Programming for Scheduling

Scheduling problems and constraint satisfaction problems are generally known to be extremely hard. This thesis proposes a new evolutionary algorithm approach to solve a constrained-based scheduling problem. In this approach, variable orderings are evolved. The variable ordering serves as a parameter for the constraint solver. Its purpose is to determine the order in which variables are labelled by the solver. Hence the evolving individuals may be encoded as permutations. Therefore, our approach can be applied to a wider range of constraint satisfaction problems. Methods for generating the initial population of individuals based on the analysis of the precedence constraints graph are proposed. New genetic operators are presented and successfully applied. Our approach succeeded in finding a range of diverse schedules with the optimal makespan. Furthermore, multi-objective optimization was successfully attempted with the NSGA-II.
In-Hand Manipulation of Objects with Unknown Shapes

This work addresses the problem of changing grasp configurations on objects with an unknown shape through in-hand manipulation. Our approach leverages shape priors, learned as deep generative models, to infer novel object shapes from partial visual sensing. The Dexterous Manipulation Graph method is extended to build incrementally and account for object shape uncertainty when planning a sequence of manipulation actions. We show that our approach successfully solves in-hand manipulation tasks with unknown objects, and demonstrate the validity of these solutions with robot experiments.
The Journal of Systems and Software

From the IoT perspective, each intelligent device can be considered as a potential source of service. Since several services perform the same function, albeit with different quality of service (QoS) parameters, service composition becomes a crucial problem to ﬁnd an optimal set of services to automate a typical business process. The majority of prior research has investigated the service composition problem with the assumption that advertised QoS values are deterministic and do not change over time. However, factors like sensors failure and network topology changes cause uncertainty in the advertised QoS values. To address this challenge, we propose a novel Anomaly-aware Robust service Composition (ARC) to deal with the problem of uncertainty of QoS values in a dynamic environment of Cloud and IoT. The proposed approach uses Bertsimas and Sim mathematical robust optimization method, which is independent of the statistical distribution of QoS values, to compose services. Moreover, our approach exploits a machine learning-based anomaly detection technique to improve the stability of the solution with a ﬁne-grained identiﬁcation of abnormal QoS records. The results demonstrate that our approach achieves 14.55% of the average improvement in ﬁnding optimal solutions compared to the previous works, such as information theory-based and clustering-based methods.
The effect of changing environmental conditions with the use of Sephadex beads on the growth of an Escherichia coli strain able to use quorum sensing (AB1157) by limiting availability of autoinducers

Bacteria communicate by releasing molecules that accumulate in dense populations. This process is known as quorum sensing, and is involved in regulating a variety of cellular processes including growth. Escherichia coli strain AB1157 cells can produce homoserine lactone (HSL) autoinducer molecules, which participate in quorum sensing. The E. coli strain DH5α can not produce the autoinducer molecules, and were used as a negative control. We attempted to determine the effect on growth of making the autoinducers unavailable to the cells by adding Sephadex beads to the media. We also experimented with changing the carbon source by supplementing the media with glucose or glycerol. Both OD600 readings and spread plate counts were used to monitor the growth of the various cultures. The pH was also monitored to detect whether fluctuations that may affect growth had occurred. The results from the two trials were inconclusive. It appears as though Sephadex may have a deleterious effect on cell growth, irrespective of the quorum sensing capacity of the cells. Fluctuations in the pH of the cultures would have also affected growth, which may have confounded our interpretation of the results. Further experimentation is required to obtain a distinct correlation between inhibition of autoinducers and growth.
Antimicrobial activity of secondary metabolites obtained with different carbon sources at different stages of the Pseudomonas growth curve isolated from Fresnillo, Zacatecas, México mineral soils

The obtention of secondary metabolites from bacterial filtrates has permitted the identification of new compounds with diverse biotechnological applications. These metabolites were generated under different conditions. Eighty-six strains of Pseudomonas were isolated from mineral soils of the central region of Zacatecas to determine if these generated secondary metabolites possess antimicrobial activity against phytopathogenic microorganisms. Afterwards, parameters, such as nutrients, were identified using seven different mediums, time of production of bioactive metabolites using growth curves, the determination of antimicrobial activity during fermentation, and their minimum inhibitory concentration (MIC). One strain of Pseudomonas was able to generate specific secondary metabolites for one or all microorganisms during different stages of the growth curve. The best phase for development of these metabolites was the stationary phase; however, in enriched media supplemented with glycerol and mannitol, less antimicrobial activity was observed than that with minimal salts medium supplemented with glucose, since in the latter, five strains were susceptible. Additionally, as the growth curve advanced, the generated metabolites were specific for one microorganism and lost activity against others. It was also determined that the MIC of the secondary metabolites generated in minimal salts medium was much lower than that obtained in enriched media supplemented with glycerol and mannitol. The Pseudomonas strain obtained from mining soils is capable of generating specific bioactive metabolites of one microorganism at different stages of growth.
Multimodal and Mixed Control of Robotic Endoscopes

Bedside robotic endoscopes render surgeons autonomous from assistants, potentially improving surgical outcome and decreasing costs. Why then have they not been widely adopted? We take a step back and first characterize classic (non-robotic) endoscope use through observations, literature and a domain expert interview. We review the literature on bedside robotic endoscopes and find that existing controls, individually, do not have the power to support both intended and appropriated endoscope uses. We thus explore combining controls to support this diversity of uses. Through an iterative cycle, we design and implement a multimodal and mixed-initiative technique that combines two user controls and one system control. Our evaluations confirm that individual controls do not satisfy the diversity of endoscope uses, and also that our technique indeed does so. Our work highlights the relevance of HCI research in the medical domain through robotic systems.
Target Recognition in SAR Images Based on Multiresolution Representations with 2D Canonical Correlation Analysis

This study proposes a synthetic aperture radar (SAR) target-recognition method based on the fused features from the multiresolution representations by 2D canonical correlation analysis (2DCCA). The multiresolution representations were demonstrated to be more discriminative than the solely original image. So, the joint classification of the multiresolution representations is beneficial to the enhancement of SAR target recognition performance. 2DCCA is capable of exploiting the inner correlations of the multiresolution representations while significantly reducing the redundancy. Therefore, the fused features can effectively convey the discrimination capability of the multiresolution representations while relieving the storage and computational burdens caused by the original high dimension. In the classification stage, the sparse representation-based classification (SRC) is employed to classify the fused features. SRC is an effective and robust classifier, which has been extensively validated in the previous works. The moving and stationary target acquisition and recognition (MSTAR) data set is employed to evaluate the proposed method. According to the experimental results, the proposed method could achieve a high recognition rate of 97.63% for the 10 classes of targets under the standard operating condition (SOC). Under the extended operating conditions (EOC) like configuration variance, depression angle variance, and the robustness of the proposed method are also quantitively validated. In comparison with some other SAR target recognition methods, the superiority of the proposed method can be effectively demonstrated.
Design and optimization of a monolithic GalnP/GalnAs tandem solar cell

We have theoretically calculated the photovoltaic conversion efficiency of a monolithic dual-junction GaInP/GaInAs device, which can be experimentally fabricated on a binary GaAs substrate. By optimizing the bandgap combination of the considered structure, an improvement of conversion efficiency has been observed in comparison to the conventional GaInP2/GaAs system. For the suggested bandgap combination 1.83 eV/1.335 eV, our calculation indicates that the attainable efficiency can be enhanced up to 40.45% (300 suns, AM1.5d) for the optimal structure parameter (1550 nm GaInP top and 5500 nm GaInAs bottom), showing promising application prospects due to its acceptable lattice-mismatch (0.43%) to the GaAs substrate.