Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining the Roots of Logistical Failures: Four Illustrations From the World of Retailing

The world of retailing has undergone deep changes over the last twenty years in terms of the organization of marketing channels. Two models are today characterized by a strong dynamism: the brick & click model and the pure player model. An important literature focuses on the logistical dimensions associated with these two models, indicating that the performance of the physical distribution service is the key to success. This article takes a different point of view by exploring logistical failures from four well-known illustrations in the retailing world that could help to better understand the supply chain issues for brick & click retailers and pure player retailers.
Post-translational regulation of Mad3p in Saccharomyces cerevisiae

Post-Translational Regulation of Mad3p in Saccharomyces cerevisiae The spindle checkpoint in eukaryotic cells maintains the integrity of the genome by ensuring equal chromosome segregation during mitosis. Mad3p is a component of the spindle checkpoint in Saccharomyces cerevisiae. Mad3p is known to be in a constitutive complex with another checkpoint component Bub3p and upon checkpoint activation it interacts with Mad2p and Cdc20p to form the mitotic checkpoint complex. Recent analysis also suggests that the Mad proteins, in addition to the direct inhibition of Cdc20p through formation of the mitotic checkpoint complex, have an additional role in the down-regulation of Cdc20p levels in the cell. The results presented in this thesis show Mad3p to be a protein that is phosphorylated during every mitosis and consequently upon spindle checkpoint activation. Such phosphorylation does not require any other checkpoint components. Experiments also show that Mad3p is phosphorylated on serine 337 by Iplip kinase in vitro and the phosphorylation of Mad3p in vivo, due to an absence of tension at the kinetochore, requires ipiip. Mad3p contains two KEN box motifs that are conserved between species. Evidence in this thesis demonstrates that mutation of either of these KEN boxes renders cells sensitive to microtubule depolymerising drugs. Further analysis of these KEN box mutants shows that Cdc20p binding is reduced in both but they can both still bind Bub3p. Mutation of the N-terminal KEN box increases the half-life of Cdc20p and consequently the total levels of Cdc20p in the cell. Cdc20p turnover is also reduced in the absence of Bubip and Bub3p, but to a lesser extent. Mutation of the second KEN box in Mad3p leads to a dominant phenotype that perturbs mitosis even in the presence of wild-type Mad3p.
A Case of Methotrexate-Associated Lymphoproliferative Disorder After Resection of an Accidentally Detected Enlarged Thyroid Tumor

A Case of Methotrexate-Associated Lymphoproliferative Disorder After Resection of an Accidentally Detected Enlarged Thyroid Tumor Masatsgu Yano1*, Daisuke Sumitani1, Masayuki Shishida1, Takafumi Oshiro1, Makoto Ochi1, Yuzo Okamoto1, Hirofumi Nakayama2 and Hideki Ohdan3 1Department of Surgery, JR Hiroshima Hospital, Hiroshima, Japan 2 Department of Pathology and Laboratory Medicine, JR Hiroshima Hospital, Hiroshima, Japan 3 Department of Gastroenterological and Transplant Surgery, Applied Life Sciences, Institute of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
A study on the effect of team support and emotional exhaustion on organizational citizenship behavior of nurses in COVID-19 pandemic: mediation by team commitments

PurposeNurses need to display organizational citizenship behavior (OCB) for taking care of patients; uninterrupted care to coronavirus disease 2019 (COVID-19) patients in a stressful situation may result in emotional exhaustion and it hinders nurses' exercise of OCB. One perceives support when positive exchanges with team leaders and members (LMX) and team and members (TMX) take place for the benefit of self and the unit and lead to a feeling of commitment to the work team; the exchange facilitates the discharge of OCB. The study aims to explore the mediation effect of team commitments on the relationship between these factors with OCB of nurses in handling COVID patients.Design/methodology/approachThe cross-sectional exercise attempts to find the impact of emotional exhaustion, LMX and TMX on the OCB of the nurses and mediating effects of team commitments on OCB; correlation analysis and multiple regressions are in use for examining the relationships. The use of Sobel test and bootstrapping exercise confirm the mediation and consistency of mediation results on a larger sample.FindingsThe paper finds that LMX, TMX and team commitments significantly relate to OCB; emotional exhaustion negatively impacts OCB and team commitments fully mediate the relationship between emotional exhaustion and OCB and partially mediate the relation between LMX and TMX with OCB.Originality/valueTests demonstrate that team commitments can neutralize the effects of emotional exhaustion resulting from handling COVID-19 patients on OCB of the nurses and is an addition to organizational behavior literature. The study also presents a model that shows how positive LMX, TMX and resultant team commitments support generating OCB and offset the impact of emotional exhaustion. Theoretical and managerial implications, limitations and scope for further research discussed in the paper.
Composite Membrane Dressings System with Metallic Nanoparticles as an Antibacterial Factor in Wound Healing

Wound management is the burning problem of modern medicine, significantly burdening developed countries’ healthcare systems. In recent years, it has become clear that the achievements of nanotechnology have introduced a new quality in wound healing. The application of nanomaterials in wound dressing significantly improves their properties and promotes the healing of injuries. Therefore, this review paper presents the subjectively selected nanomaterials used in wound dressings, including the metallic nanoparticles (NPs), and refers to the aspects of their application as antimicrobial factors. The literature review was supplemented with the results of our team’s research on the elements of multifunctional new-generation dressings containing nanoparticles. The wound healing multiple molecular pathways, mediating cell types, and affecting agents are discussed herein. Moreover, the categorization of wound dressings is presented. Additionally, some materials and membrane constructs applied in wound dressings are described. Finally, bacterial participation in wound healing and the mechanism of the antibacterial function of nanoparticles are considered. Membranes involving NPs as the bacteriostatic factors for improving wound healing of skin and bones, including our experimental findings, are discussed in the paper. In addition, some studies of our team concerning the selected bacterial strains’ interaction with material involving different metallic NPs, such as AuNPs, AgNPs, Fe3O4NPs, and CuNPs, are presented. Furthermore, nanoparticles’ influence on selected eukaryotic cells is mentioned. The ideal, universal wound dressing still has not been obtained; thus, a new generation of products have been developed, represented by the nanocomposite materials with antibacterial, anti-inflammatory properties that can influence the wound-healing process.
El Estigma Social Asociado a la Enfermedad de Chagas

Objetivos: identificar a partir de relatos individuales y familiares los componentes del estigma social asociado a un diagnóstico de Chagas positivo. Métodos: el estudio recopila los testimonios de tres familias a través de entrevistas a profundidad que fueron grabadas, cuyo contenido fue estructurado y luego compartido entre los investigadores a través de un proceso de triangulación. Resultados: se identificaron las diferentes formas de estigma social, experimentado, percibido, anticipado, así como el autoestigma, el estigma por asociación y comportamientos de discriminación; lo que conlleva el aislamiento social, refuerza los miedos tradicionalmente relacionados a esta enfermedad, y provoca tensiones intrafamiliares. El estigma social y el silencio que lo acompaña son serias barreras de acceso a la consulta médica y al tratamiento antiparasitario Conclusiones: Es importante tomar en cuenta aspectos de tipo psico-socio-cultural en las estrategias de atención integral de Chagas, principalmente en los programas de información, educación, comunicación (IEC) y durante la consulta médica. Para romper el estigma y el silencio que lo acompaña, es indispensable integrar las personas afectadas por Chagas y otros actores de la sociedad civil en el diseño de esas estrategias.
Deep Graph Reinforcement Learning Based Intelligent Traffic Routing Control for Software-Defined Wireless Sensor Networks

Software-defined wireless sensor networks (SDWSN), where the data and control planes are decoupled, are more suited to handling big sensor data and effectively monitoring dynamic environments and events. To overcome the limitations of using static routing tables under high traffic intensity, such as network congestion, high packet loss rate, low throughput, etc., it is critical to design intelligent traffic routing control for the SDWSNs. In this paper we propose a deep graph reinforcement learning (DGRL) model-based intelligent traffic control scheme for SDWSNs, which combines graph convolution with deterministic policy gradient. The model fits well for the task of intelligent routing control for the SDWSN, as the process of data forwarding can be regarded as the sampling of continuous action space and the traffic data has strong graph features. The intelligent control policies are made by the SDWSN controller and implemented at the sensor nodes to optimize the data forwarding process. Simulation experiments performed on the Omnet++ platform show that, compared with the existing traffic routing algorithms for SDWSNs, the proposed intelligent routing control method can effectively reduce packet transmission delay, increase packet delivery ratio, and reduce the probability of network congestion.
GNSS-SDR: An Open Source Tool for Researchers and Developers

This paper introduces GNSS-SDR, an open source Global Navigation Satellite System software-defined receiver. The lack of reconfigurability of current commercial-off-the-shelf receivers and the advent of new radionavigation signals and systems make software receivers an appealing approach to design new architectures and signal processing algorithms. With the aim of exploring the full potential of this forthcoming scenario with a plurality of new signal structures and frequency bands available for positioning, this paper describes the software architecture design and provides details about its implementation, targeting a multiband, multisystem GNSS receiver. The result is a testbed for GNSS signal processing that allows any kind of customization, including interchangeability of signal sources, signal processing algorithms, interoperability with other systems, output formats, and the offering of interfaces to all the intermediate signals, parameters and variables. The source code release under the GNU General Public License (GPL) secures practical usability, inspection, and continuous improvement by the research community, allowing the discussion based on tangible code and the analysis of results obtained with real signals. The source code is complemented by a development ecosystem, consisting of a website (www.gnss-sdr.org), as well as a revision control system, instructions for users and developers, and communication tools.
Online Learning Assessment: Solution in Industrial Revolution 4.0

This study aimed to determine the effectiveness, advantages, and disadvantages of using digital platform in learning assessment. The digital platform discussed in this study is Eduprime, a digital platform that is engaged in assessment. This research uses the mixed method. Data retrieval is done by interview techniques, student questionnaires, and documentation using google forms. The instruments used were interview sheets and student questionnaires. The sample of this research is the principal, homeroom teacher, and teacher of SMA Mandiri Balaraja, as many as 7 respondents, and grade 11 th and 12 th students of SMA Mandiri Balaraja, totaling 131 respondents. Based on the results of the study, some students stated that the use of digital platforms in the evaluation of learning gave a positive response. This is evidenced by the average percentage of 71.36% in the good category. Meanwhile, the principal, homeroom teachers, and teachers said that the use of the digital platform (Eduprime) was practical, also said some advantages, disadvantages, and suggestions for learning assessment activities.
Transient Performance Improvement in the Boundary Control of Boost Converters using Synthetic Optimized Trajectory

This paper focuses on an improvement in the transient performance of Boost converters when the load changes abruptly. This is achieved on the basis of the nature trajectory in Boost converters. Three key aspects of the transient performance are analyzed including the storage energy change law in the inductors and capacitors of converters during the transient process, the ideal minimum voltage deviation in the transient process, and the minimum voltage deviation control trajectory. The changing relationship curve between the voltage deviation and the recovery time is depicted through analysis and simulations when the load suddenly increases. In addition, the relationship curve between the current fluctuation and the recovery time is obtained when the load suddenly decreases. Considering the aspects of an increasing and decreasing load, this paper proposes the transient performance synthetic optimized trajectory and control laws. Through simulation and experimental results, the transient performances are compared with the other typical three control methods, and the ability of proposed synthetic trajectory and control law to achieve optimal transient performance is verified.
An Application with Jetson Nano for Plant Stress Detection and On-field Spray Decision

Increasing field productivity is not just a financial need, but also a social issue. Several technologies converge to promote food production and, in this context, the fog computing paradigm can support the development of solutions for precision agriculture. This paper proposes an application of the Jetson Nano device, embedded in an agricultural spraying implement. This device supports the decision on irrigation activity, based on data collected by sensors distributed in the field. The sensors read information about the plant’s stress level from electrical signals and the Jetson Nano enables real-time analysis, through machine learning algorithms, to manage the product spray rate, according to the condition of the crop. Initial studies validated the proposed solution on an experimental basis, showing that the device can be an alternative for this purpose, since it can be used efficiently in machine learning tasks from data collected by the sensors. The experiment also highlighted some limitations of the proposed solution, such as the importance of observing the conditions of the system as a whole, its context and environment, in order to improve performance in spraying process.
Generation of Data-Driven Expected Energy Models for Photovoltaic Systems

Although unique expected energy models can be generated for a given photovoltaic (PV) site, a standardized model is also needed to facilitate performance comparisons across fleets. Current standardized expected energy models for PV work well with sparse data, but they have demonstrated significant over-estimations, which impacts accurate diagnoses of field operations and maintenance issues. This research addresses this issue by using machine learning to develop a data-driven expected energy model that can more accurately generate inferences for energy production of PV systems. Irradiance and system capacity information was used from 172 sites across the United States to train a series of models using Lasso linear regression. The trained models generally perform better than the commonly used expected energy model from international standard (IEC 61724-1), with the two highest performing models ranging in model complexity from a third-order polynomial with 10 parameters (Radj2 = 0.994) to a simpler, second-order polynomial with 4 parameters (Radj2=0.993), the latter of which is subject to further evaluation. Subsequently, the trained models provide a more robust basis for identifying potential energy anomalies for operations and maintenance activities as well as informing planning-related financial assessments. We conclude with directions for future research, such as using splines to improve model continuity and better capture systems with low (≤1000 kW DC) capacity.
Slovak-English Vocalic Approximation

Besides the dominating behaviorist and structuralist theories of the Second Language Acquisition a new concept of the second language (L2) acquisition was formulated in the 1960s – the theory of interlanguage [1–5]. Some other names used for the interlanguage phenomenon are: transitive competence [1], approximative system [4], idiosyncratic dialect [6], multicompetence [7], transmitting or the third system [8].
Applications of HYDRUS and the Proposed SWMRUM Software in Simulating Water Flow with Root Water Uptake Through Soils

Numerical models are frequently used for simulation of water movement in soils. Soil water flow simulation models require a description of root water uptake as a sink term. In this study, two water flow models including the proposed SWMRUM model and the HYDRUS software were compared based on the field measurement in an apple orchard. Probe-type time domain reflectometry (TDR) was used to measure soil volumetric water content within radial (R) and depth (Z) vectors. Root water uptake model includes root density distribution function, potential transpiration and soil water stress-modified factor. A root water uptake sink term was developed, and entered into a soil water dynamic model to enable simulation of water flow in soil via numerical solution of Richards equation. The outputs from the two models were compared against the measured water content data. Simulated and measured water contents were in excellent agreement. Analysis of residual errors, differences between the measured and simulated values, was performed to evaluate the model performance, based on the maximum error (ME), root mean square error (RMSE), coefficient of determination (CD), modeling efficiency (EF), and coefficient of residual mass (CRM). Results showed that maximum root water uptake was 0.04 m 3 m -3 d -1 at 25-30 cm depth and the minimum was 0.005 m 3 m -3 d -1 at 80 cm depth.
Qualifications or Soft Skills? Studying Job Advertisements for Demand for Low-Skilled Staff in Slovakia

This paper analyses job advertisements to identify the specific skills and characteristics that are demanded in the Slovak labour market in selected low- and medium-skilled occupations in different sectors. It is innovative in exploring online job advertisement data and in quantifying the different skills, personal attributes and characteristics requested by employers. The authors find that Slovak employers are fairly demanding in the low- and medium-level-skilled sectors in terms of skill sets, skill intensity and formal educational levels; an ‘ideal’ low- to medium-skilled job-seeker in Slovakia needs to demonstrate a considerable set of skills and qualities. From the skills analysed, non-cognitive skills and specific cognitive skills were demanded more than general cognitive skills or appearance. Experience was the single most requested characteristic. The study shows that online portals that collect information about demand can be a very useful source of data about the content and specificities of demand at the micro-level. Empirical analyses of this type could thus be a valuable source of information for education, training policies and labour market policies.
Climatic changes in India – (II) Temperature

Annual mean maximum and minimum temperature data of 30 meteorological stations distributed over India and Pakistan for which long and continuous records available are examined for (i) long terms trends (ii) short period oscillations and (iii) random or unsystematic components. The stations jon the west coast of India and the sub-Himalayan regions of month and northeast India have a tendency for increasing maximum temperature and those in the rest of the country extending in a northwesterly direction from north Madras coast to Baluchistan have a tendency for decreasing maximum temperature. In regards to minimum temperature except for a small strip extending from Orissa to the Vindhyas\, the c9ountry has a tendency for increasing minimum temperature.
Navigating an Automated Driving Vehicle via the Early Fusion of Multi-Modality

The ability of artificial intelligence to drive toward an intended destination is a key component of an autonomous vehicle. Different paradigms are now being employed to address artificial intelligence advancement. On the one hand, modular pipelines break down the driving model into submodels, such as perception, maneuver planning and control. On the other hand, we used the end-to-end driving method to assign raw sensor data directly to vehicle control signals. The latter is less well-studied but is becoming more popular since it is easier to use. This article focuses on end-to-end autonomous driving, using RGB pictures as the primary sensor input data. The autonomous vehicle is equipped with a camera and active sensors, such as LiDAR and Radar, for safe navigation. Active sensors (e.g., LiDAR) provide more accurate depth information than passive sensors. As a result, this paper examines whether combining the RGB from the camera and active depth information from LiDAR has better results in end-to-end artificial driving than using only a single modality. This paper focuses on the early fusion of multi-modality and demonstrates how it outperforms a single modality using the CARLA simulator.
Pembentukan Jaringan Lunak Saat Pencetakan Implan dengan Laser Diode

Background: Currently, the development of lasers in the medical world of dentistry is very rapid. There are many treatments in dentistry that we can use with lasers, one of which is implants. An effective, practical, and safe laser method for treatment in and around implants that requires soft tissues to either expose the implant for the restorative phase or reshape the gingival margin for aesthetics is the Diode Laser. Case report: a woman wants to have an implant placed on tooth 26 so that she can chew well and the other teeth do not shift. The implant installation technique with 2 stages of surgery can only be done one year later due to the covid 19 pandemic. The gingival opening is done using laser diode for healing installation with a diameter of 5 mm and 5 mm in height. Installation of healing is done without suturing because the diode laser method is minimally invasive and gives a good healing result for the soft tissue Conclusion: The diode laser method is very effective and safe for soft tissue formation during implant treatment it is minimally invasive.