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Correlation of Vitamin D and Core Stabilization Exercise in Low Back Pain: A Narrative Review
No full textBackground and Aim: Low back pain is a complex condition that can have various causes and its
management involves multiple treatment strategies as per the cause. Use of vitamin D
supplementation for LBP has gained attention due to its anti-inflammatory effect and helps to
improves bone density whereas core stabilization exercises can help to strengthen core and spinal
muscles and stabilize the spine. While there is evidence to suggest that both Vitamin D and core
stabilization exercise may have potential benefits for low back pain, the direct correlation between
these two factors is not well established. So the aim of this narrative review is to find out the
correlation of Vitamin D and Core Stabilization exercise in low back pain.
Methods: We searched the articles using PubMed and Google Scholar regarding the correlation of
Vitamin D and Core Stabilization exercise in male and female low back pain subjects.
Results: Evidence from human studies suggest that Vitamin D and core stabilization exercises both
are important for overall functioning of intervertebral disc integrity and its stability. Vitamin D is a
vital nutrient that plays a critical role in maintaining bone health, regulating the immune system, and
reducing inflammation whereas Core stabilization exercises improves core and spinal muscle
strength that stabilizes the spine.
Conclusions: Clinicians caring for patients must be aware of this Vitamin D and Core stabilization
exercises to find the right treatment course for each patient. In many cases quick Vitamin D
supplementation along with Core stabilization exercises may be used to manage LBP. While there
is a rightful role for Vitamin D in management of lumbar low back pain, non-pharmacological
options like Core stabilization exercises should also be considered as they can play an important role
in physiotherapy management of low back pain
Relationship Between Back Pain and Job Satisfaction among Teachers in Kelantan
No full textBack pain is one of the most common health problems experienced among individuals,
particularly among those who have jobs that require them to sit, stand or perform physically
demanding activities for long hours. Teachers are one such group of professionals who are at
higher risk of developing back pain due to the nature of their jobs. This has been acknowledged
as a significant problem that can impact the job satisfaction of the teaching profession. This
study aimed to identify the relationship between back pain and job satisfaction among teachers.
This study examines on how back pain is related to the level of job satisfaction among teachers
in Kelantan. A cross-sectional study was conducted among randomly selected teachers from
thirty-four primary schools in Tanah Merah, Kelantan from December to February 2023. The
level of lower back pain was assessed using an Oswestry Low Back Pain Disability, while for
Teacher satisfaction scale (TJSS) was used to examine the teacher satisfaction level. The
response rate of this study was 100% (n=208). The majority of respondents are females
(n=170,81.7%), Malay(n=174,83.7%), married(n=163,78.4%), aged between 30- 39 years
old(n=64,31.3%),40-49 years old(n=119,57.2%) and have more than 10 years of work
experience. The level of back pain and job satisfaction among teachers (r=-.129,
95%CI=1.6970, 1.9059, P-value= .064) were no significant correlation between two variables.
There is insufficient evidence to conclude that back pain among teachers is directly related to
job satisfaction. Teaching may be physically stressful and teachers often experience high levels
of stress and burnout. However, the findings on relationship between back pain and job
satisfaction are not related
Rest API Implementation on Presence System using QR-Code and Web-Based Haversine Formula Method
No full textStudent presence is one of the most important things in lecturing. However, the student attendance
system at Langlangbuana University currently still uses a manual system in which students sign
the attendance sheet provided. The attendance list system has several weaknesses, namely the
vulnerability to the safekeeping of student attendance lists, loss or damage to the attendance sheet,
and the use of a relatively long time so that the manual attendance process as a whole becomes
inefficient. In order to minimize these weaknesses, we need a system that can process student
attendance lists. There are technologies that can be used to reduce these cases, one of which is QR�Code, which uses the REST API for the student attendance list system so that later students can
carry out the attendance list process by scanning the QR code provided in the application. With
this application, it will be easier for lecturers to manage attendance lists and for students to make
attendance
The Effects of Self Mobilization Technique on Pain and Headache in Patients with Cervicogenic Headache: A Four Week Randomized Clinical Trial
No full textIntroduction: Cervicogenic headache accounts for 15-20% of all chronic and recurrent headaches
and it affects 2.2-2.5% of the adult population. It is characterized by unilateral pain originating from
the occipital region without side shifts and it is often related to the skeletal and muscular structures
of the cervical spine. The zygapophyseal joints of the upper cervical spine are the most frequent
contributors for cervicogenic headache. Manual therapy and exercises have been proposed as the
initial treatment option addressing the root cause of the problem. This study aims to evaluate the
effectiveness of self-mobilization among cervicogenic patients on Numeric Pain Assessment Scale
and Headache Disability Index. Methods: Single blinded, randomized clinical trial was done by
recruiting 33 subjects. Subjects were clinically diagnosed with chronic headache and mechanical
neck pain from KPJUC groups were randomly allocated into two groups using lottery ticket
randomization chosen from a concealed container. Subjects were evaluated on a weekly basis for
four continuous weeks. Results: Repeated measure ANOVA was used to analyze the effects of the
self-SNAG. Significant improvement in pain and HDI scoring were established with p<0.05 within
the experimental and control group. However, statistical differences between the control and
experimental group were not established but, notable differences in mean and standard deviation
were recorded in experimental group compared to control group between baseline and subsequent
weeks. Estimated marginal means reveals experimental group shows better improvement compared
to the control group over the four weeks. Conclusion: The findings suggest that Mulligans self�SNAG is effective. The intensity of pain reduced in subjects and the HDI scoring indicated
improvement
Multiple Linear Regression for Predicting the Ship Booking Time: A Case Study at PT. Samudera Indonesia
No full textA statistical method called multiple linear regression (MLR), or just multiple regression, makes use of many explanatory variables to forecast the value of a response variable. We studied PT. Samudera Indonesia, a company in the shipping sector, for this paper. One of the companies providing services for maritime transportation is this one, which deals with the inflow and outflow of commodities. Our study focuses on the application of ship docking time prediction at PT. Samudera Indonesia, which is situated at Boom Baru port in Palembang. This research makes use of historical data on the ship's docking time during the preceding three (3) years, utilizing multiple linear regression techniques. Using the company's dataset for the years 2018 to 2020 which consists of 70% training data and 30% testing data the experiment was conducted and recorded. The model's performance has yielded very positive results, as evidenced by the 1.132 RSME (root mean square error) number, 1.075 absolute error, and 1.01% relative error. These numbers closely matched the initial figures that the company had documented
Geotechnical Properties Improvement of Erosion Susceptible Soil with Caustic Soda (A Case Study of Ekosodin, Benin City)
No full textThe presence of the University of Benin (UNIBEN) makes the Ekosodin
community economically vital, with local businesses benefiting from the spending of
students and staff. Consequently, it is essential to address the problem of soil erosion in the
area to facilitate ongoing development and growth. The aim of this study was achieved by
collecting four soil samples and analysing various properties such as specific gravity, particle
size distribution, Atterberg limits, optimum moisture content, maximum dry density,
cohesion, angle of internal friction, and California bearing ratio. The study also examined the
impact of adding caustic soda at different concentrations. The resulting unstabilized soil
exhibited AASHTO class A-6 and A-7-6 characteristics, featuring a significant proportion of
clayey soil with more than 35% passing through sieve No 200, resulting in a fair to poor
subgrade rating in pavement design and significant compressibility. Nevertheless, as the
percentage of caustic soda increased, there was a reduction in the liquid limit, plastic limit,
plasticity index, optimum moisture content, and angle of internal friction. Additionally,
higher maximum dry density, cohesion, unsoaked and soaked California Bearing Ratio
(CBR) values were recorded with increased caustic soda content. The highest soaked soil
CBR value of 26.0% was achieved with a 10% caustic soda stabilization. Therefore, chemical
stabilization using caustic soda is recommended for erosion-prone soil in Ekosodin, as it
transforms the area's soil from a poor subgrade or foundation to a robust load-bearing material
suitable for building and road construction
The Analysis of Joint Inspection Repository System and The Proposed Solution
No full textTechnology advancements indicate that labor performed by humans is now more easily
accomplished. Initially, this was carried out conventionally at the business where we studied report
management and storage at PT. Kereta Api Indonesia Regional Division III. In this perspective,
we suggested a solution based on the study that revealed the creation of a new system known as
the Web-based Repository Joint Inspection System was judged required to facilitate staff members'
handling, storing, and monitoring of current reports (for managers). The four (4) distinct user
groups or access levels in this system are Administrator, User, Manager, and Safety. The Rational
Unified Process, or RUP, was the development approach employed for this system. Still, this
section goes into great detail about the uploading, downloading, and deleting of data. Following
the upload, download, and removal of files, the system must be examined to make sure it is
operational. Both feature testing and the black box method are used to test this system. It is possible
to develop test scenarios based on how the system works
THEORETICAL CONCLAVE: ARE SALES VISIONARIES SHAPING TOMORROW'S SALES LANDSCAPE?
No full textThis article delves into an analysis of motivation theories within the context of personal selling,
exploring their implications for the development and optimization of salesperson compensation
plans. The initial section reviews prominent motivation theories, offering insights into their
principles and applications. Subsequently, the article transitions to a discussion on the practical
utilization of these theories in the design and implementation of compensation structures for sales
professionals. By examining the intersection of motivation theories and salesperson compensation,
this article aims to contribute valuable perspectives to the ongoing discourse in sales management
and organizational behavior. The findings presented herein offer a nuanced understanding of how
motivational factors can be strategically harnessed to enhance sales performance and align with
broader organizational objectives
The Holistic Archival Personality Profiling Model (HAPPM): Comprehensive Data Integration for Personality Analysis
No full textThe traditional approach to biographical profiling, predominantly reliant on limited and
fragmented datasets, has frequently resulted in superficial personality understandings. This is
largely due to an overemphasis on official records and notable events, neglecting the rich tapestry
of everyday experiences and personal interactions that significantly shape personalities. To address
this shortcoming, this article introduces a multi-disciplinary methodology, The Holistic Archival
Personality Profiling Model (HAPPM), which integrates a diverse array of archival materials,
including personal correspondences, social media footprints, and family memorabilia. This
approach involves digitizing various data forms, including handwritten documents, into machine-readable text, and then semantically classifying this data with biotags, chronotags, and geotags for
organization within specific spatial and temporal contexts. Such comprehensive data aggregation
establishes a more accurate "space-time continuum" for individuals, enhancing our understanding
of their lives. The innovative aspect of HAPPM is the utilization of large language models to
"converse" with the data, facilitating a more holistic representation of personalities. Preliminary
results from applying HAPPM have shown its efficacy in uncovering previously unknown aspects
of individual lives, offering insights into personal beliefs, daily routines, and social interactions.
This has been validated through comparative analysis with existing biographical data, revealing a
more complete and nuanced understanding of personalities. Therefore, HAPPM marks a
significant advancement in personality profiling, capturing not only the grandiose but also the
mundane, and offering a comprehensive tool for researchers and historians to explore the full
spectrum of human experienc
Analysis of Feature Selection Methods for Sentiment Analysis Concerning Covid-19 Vaccination Issues
No full textSentiment analysis or opinion mining is a computational study of a person's opinions, sentiments,
evaluations, attitudes, moods, and emotions. Sentiment analysis is one of the most active research
areas in natural language processing, data mining, information retrieval, and web mining. One of
the problems identified in the sentiment analysis process is the massive amount of data or text
properties. In sentiment analysis, each word or term is collected into properties or dimensions,
forming a data table. Due to the vast number of terms, this causes the process to take too long and
requires a computer with tremendous power or ability. In addition, this can lead to a decrease in
the quality of the model because data that is too large will also provide a significant bias value.
Not all terms have contributions or relationships to decisions or labels in the form of positive,
negative, and neutral values. For this reason, the feature selection method will be used in this study
to select features or terms that contribute more to decisions or labels. It is also hoped that this can
increase the quality of the prediction model that will be formed. In this study, the author will
continue the research from another researcher by adding a feature selection process, such as two
algorithms from the filtered method, chi-square, and information gain, and one algorithm from the
wrapped method, which is Genetic Algorithms (GA). The experiment result shows that the GA
obtained result has the highest accurate value compared to the other methods