The Impact of Training on Improving Employee Performance: A Case Study on Employees in the Directorate of Education of Ma'an District

Purpose: The aim of this study is to determine the impact of training on improving the performance of workers in Maan's Directorate of Education.   Theoretical framework: This study will focus on finding a cognitive dimension that contributes to clarifying the concept of training and its dimensions (type of training, training period, trainers) and its impact on the job performance of employees.   Design/Methodology/Approach: The descriptive analytical approach was used in the study. The study sample included 34 male and female employees; 40% of the study population. The data was collected using a questionnaire designed by the researcher after its validity and reliability have been tested. The questionnaire contained (27) items distributed across the following dimensions: training quality (7) items, training duration (6) items, trainers (7) items, and performance (7) items.   Findings: The results of the simple regression analysis revealed that overall training has a moderate effect on improving worker performance. Furthermore, the results of the multiple regression analysis revealed that there is a statistically significant effect in improving worker job performance due to the trainers’ dimension, but no effect in improving performance through the other two dimensions (quality training, duration of training). The results also revealed that there were no statistically significant differences in the responses of the study sample based on gender.   Research, Practical & Social implications: The study helps the directorate of education of Ma’an District to understandthe impact of training on improving employee performance. It will also help the employees realize the effect of training on their performance.   Originality/Value: The value of the study is represented in being the first study to be applied on the employees of Ma’an District. Therefore, it is a contribution to to the Human Resource/Training Department to understand the impact of training on improving employee performance.

Evaluation of Bearing Fault Detection on Different _K-Folds using Deep Learning Ensemble Models

One of the most crucial parts of contemporary machinery and industrial equipment is the induction motor. Therefore, it is essential to create a fault diagnosis system that can identify induction motor problems and operating circumstances before they become serious. In this study, an induction motor's defect diagnosis is carried out in three different states, including normal, rotor fault, and bearing fault. The suggested fault diagnostic system is also described, along with a GUI. The experimental findings support the suitability of the suggested approach for rotor and bearing defects in induction motor diagnosis. A GUI for defect diagnostics was also created and used in a real-world setting. We have used Chi-Square method for high score attributes values. For the normal, rotor fault, and bearing fault states of induction motors identified by DBN, CNN, SNN, SVM and RF respectively, the fault detection system's accuracy in the actual world. In the experiment, we find Algorithms model-II, K-Folds (5, 10 & 15) , Accuracy (%), Training loss, Validation loss value for RF-SVM-CNN are 89.2, 0.260013, 0.304936 for k fold 5, 98.4, 0.155960, 0.154133 for k-fold 10 and 98.3, 0.155759, 0.144127 for k- fold 15 respectively

An analytical study of critical factors affecting contractor efficiency in construction projects in Indian scenario

Purpose: Recent studies show that lowest bidder technique is mainly used in developing countries such as India to award a contract. It has been demonstrated that the lowest bid is not always the accurate one and can lead to cost overruns and time extensions amongst other problems. The aim of this study was to investigate the critical factors impacting contractor’s efficiency in Indian construction projects. Research approach: A survey was sent to participants of construction projects awarded by the government with the lowest bidder technique in Uttar Pradesh, India. For further research, snowball sampling was used, and structured interviews were conducted amongst experienced managers and engineers of these projects on both client’s and contractor’s side. Findings: It was observed that, to a greater extent, the delays were caused due to contractor’s opportunistic behaviour. The main findings are that new bidding methodologies are to be tested as they can lead to the choice of a more accurate and realistic bidder. In addition, subjective evaluation components, such as schedule and workforce, should be reflected in contract award methods in addition to the cost criteria. Further studies should be performed on the choice of contract awarding methodology based on the project size and type. Originality value: The researcher’s focus was to analyze the influence of contracting methodologies and factors affecting contractor’s performance in lowest bid award project, where this is an area of least focus amongst researchers in the Indian subcontinent

A comprehensive review on the techniques for extraction of bioactive compounds from medicinal cannabis

Cannabis is well-known for its numerous therapeutic activities, as demonstrated in pre-clinical and clinical studies primarily due to its bioactive compounds. The Cannabis industry is rapidly growing; therefore, product development and extraction methods have become crucial aspects of Cannabis research. The evaluation of the current extraction methods implemented in the Cannabis industry and scientific literature to produce consistent, reliable, and potent medicinal Cannabis extracts is prudent. Furthermore, these processes must be subjected to higher levels of scientific stringency, as Cannabis has been increasingly used for various ailments, and the Cannabis industry is receiving acceptance in different countries. We comprehensively analysed the current literature and drew a critical summary of the extraction methods implemented thus far to recover bioactive compounds from medicinal Cannabis. Moreover, this review outlines the major bioactive compounds in Cannabis, discusses critical factors affecting extraction yields, and proposes future considerations for the effective extraction of bioactive compounds from Cannabis. Overall, research on medicinal marijuana is limited, with most reports on the industrial hemp variety of Cannabis or pure isolates. We also propose the development of sustainable Cannabis extraction methods through the implementation of mathematical prediction models in future studies

A novel distributed authentication of blockchain technology integration in IoT services

Internet of Things (IoT) is currently playing a major role in how intelligent devices are interconnected and deployed to automate services in transport and smart living sectors. However, IoT is facing challenges in terms of data protection and authentication due to the heterogeneous nature of IoT devices that do not exhibit a central authority. It is crucial to provide secure and trustworthy solutions for the increasing demands of decentralized IoT environments. To this end, this research proposes a novel integration of blockchain-technologies in IoT services to enhance security, data integrity, users privacy, system scalability and interoperability of devices. This is done by leveraging smart contracts to enforce authentication, access control and data exchange mechanisms for IoT devices. The proposed approach is verified by the construction and deployment of a smart contract over the Polygon blockchain network in a simulated real-world IoT scenario. The obtained results show that the proposed approach ensures fast and secure authentication in IoT networks by decreasing the risk of unauthorized access and data tampering

Band Edge Tailoring in Few-Layer Two-Dimensional Molybdenum Sulfide/Selenide Alloys

Chemical alloying is a powerful approach to tune the electronic structure of semiconductors and has led to the synthesis of ternary and quaternary two-dimensional (2D) dichalcogenide semiconductor alloys (e.g., MoSSe₂, WSSe₂, etc.). To date, most of the studies have been focused on determining the chemical composition by evaluating the optical properties, primarily via photoluminescence and reflection spectroscopy of these materials in the 2D monolayer limit. However, a comprehensive study of alloying in multilayer films with direct measurement of electronic structure, combined with first-principles theory, is required for a complete understanding of this promising class of semiconductors. We have combined first-principles density functional theory calculations with experimental characterization of MoS_(2(1-x))Se_(2x) (where x ranges from 0 to 1) alloys using X-ray photoelectron spectroscopy to evaluate the valence and conduction band edge positions in each alloy. Moreover, our observations reveal that the valence band edge energies for molybdenum sulfide/selenide alloys increase as a function of increasing selenium concentration. These experimental results agree well with the results of density functional theory calculations showing a similar trend in calculated valence band edges. Our studies suggest that alloying is an effective technique for tuning the band edges of transition-metal dichalcogenides, with implications for applications such as solar cells and photoelectrochemical devices

Neurobrucellosis with transient ischemic attack, vasculopathic changes, intracerebral granulomas and basal ganglia infarction: a case report

<p>Abstract</p> <p>Introduction</p> <p>Central nervous system involvement is a rare but serious manifestation of brucellosis. We present an unusual case of neurobrucellosis with transient ischemic attack, intracerebral vasculopathy granulomas, seizures, and paralysis of sixth and seventh cranial nerves.</p> <p>Case presentation</p> <p>A 17-year-old Caucasian man presented with nausea and vomiting, headache, double vision and he gave a history of weakness in the left arm, speech disturbance and imbalance. Physical examination revealed fever, doubtful neck stiffness and left abducens nerve paralysis. An analysis of his cerebrospinal fluid showed a pleocytosis (lymphocytes, 90%), high protein and low glucose levels. He developed generalized tonic-clonic seizures, facial paralysis and left hemiparesis. Cranial magnetic resonance imaging demonstrated intracerebral vasculitis, basal ganglia infarction and granulomas, mimicking the central nervous system involvement of tuberculosis. On the 31st day of his admission, neurobrucellosis was diagnosed with immunoglobulin M and immunoglobulin G positivity by standard tube agglutination test and enzyme-linked immunosorbent assay in both serum and cerebrospinal fluid samples (the tests had been negative until that day). He was treated successfully with trimethoprim and sulfamethoxazole, doxycyline and rifampicin for six months.</p> <p>Conclusions</p> <p>Our patient illustrates the importance of suspecting brucellosis as a cause of meningoencephalitis, even if cultures and serological tests are negative at the beginning of the disease. As a result, in patients who have a history of residence or travel to endemic areas, neurobrucellosis should be considered in the differential diagnosis of any neurologic symptoms. If initial tests fail, repetition of these tests at appropriate intervals along with complementary investigations are indicated.</p

The Pioneer Anomaly

Radio-metric Doppler tracking data received from the Pioneer 10 and 11 spacecraft from heliocentric distances of 20-70 AU has consistently indicated the presence of a small, anomalous, blue-shifted frequency drift uniformly changing with a rate of ~6 x 10^{-9} Hz/s. Ultimately, the drift was interpreted as a constant sunward deceleration of each particular spacecraft at the level of a_P = (8.74 +/- 1.33) x 10^{-10} m/s^2. This apparent violation of the Newton's gravitational inverse-square law has become known as the Pioneer anomaly; the nature of this anomaly remains unexplained. In this review, we summarize the current knowledge of the physical properties of the anomaly and the conditions that led to its detection and characterization. We review various mechanisms proposed to explain the anomaly and discuss the current state of efforts to determine its nature. A comprehensive new investigation of the anomalous behavior of the two Pioneers has begun recently. The new efforts rely on the much-extended set of radio-metric Doppler data for both spacecraft in conjunction with the newly available complete record of their telemetry files and a large archive of original project documentation. As the new study is yet to report its findings, this review provides the necessary background for the new results to appear in the near future. In particular, we provide a significant amount of information on the design, operations and behavior of the two Pioneers during their entire missions, including descriptions of various data formats and techniques used for their navigation and radio-science data analysis. As most of this information was recovered relatively recently, it was not used in the previous studies of the Pioneer anomaly, but it is critical for the new investigation.Comment: 165 pages, 40 figures, 16 tables; accepted for publication in Living Reviews in Relativit

Code Status Discussions Between Attending Hospitalist Physicians and Medical Patients at Hospital Admission

BackgroundBioethicists and professional associations give specific recommendations for discussing cardiopulmonary resuscitation (CPR).ObjectiveTo determine whether attending hospitalist physicians' discussions meet these recommendations.DesignCross-sectional observational study on the medical services at two hospitals within a university system between August 2008 and March 2009.ParticipantsAttending hospitalist physicians and patients who were able to communicate verbally about their medical care.Main measuresWe identified code status discussions in audio-recorded admission encounters via physician survey and review of encounter transcripts. A quantitative content analysis was performed to determine whether discussions included elements recommended by bioethicists and professional associations. Two coders independently coded all discussions; Cohen's kappa was 0.64-1 for all reported elements.Key resultsAudio-recordings of 80 patients' admission encounters with 27 physicians were obtained. Eleven physicians discussed code status in 19 encounters. Discussions were more frequent in seriously ill patients (OR 4, 95% CI 1.2-14.6), yet 66% of seriously ill patients had no discussion. The median length of the code status discussions was 1 min (range 0.2-8.2). Prognosis was discussed with code status in only one of the encounters. Discussions of patients' preferences focused on the use of life-sustaining interventions as opposed to larger life goals. Descriptions of CPR as an intervention used medical jargon, and the indication for CPR was framed in general, as opposed to patient-specific scenarios. No physician quantitatively estimated the outcome of or provided a recommendation about the use of CPR.ConclusionsCode status was not discussed with many seriously ill patients. Discussions were brief, and did not include elements that bioethicists and professional associations recommend to promote patient autonomy. Local and national guidelines, research, and clinical practice changes are needed to clarify and systematize with whom and how CPR is discussed at hospital admission

Artificial intelligence for dementia genetics and omics

Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high-dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia-related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts. Ultimately AI approaches improve our ability to interrogate genetics and omics data for precision dementia medicine