Miracle-dz/UniFAR-FTUs huggingface dataset:
A Retrospective Study to Identify the Causes of Post-Natal Depression among Post-Natal Mothers of a Selected Hospital at Bharuch, Gujarat

The birth of a baby can trigger a jumble of powerful emotions, from excitement and joy to fear and anxiety. But it can also result in something you might not expect-depression. Post-natal depression is a type of depression that many parents experience after having a baby. It is a common problem, affecting more than 1 in every 10 women within a year of giving birth. Post-partum depression is not a character Á aw or a weakness. Sometimes it is simply a complication of giving birth. In post-partum depression, prompt treatment can mitigate the symptoms and help develop bonds with baby. The aim of this study was to determine the causes of post-partum depression among post-natal mothers from selected hospital at Bharuch using Edinburgh Post-natal Depression Scale Score (EPDS). In this retrospective study endeavour was made to assess the level of post-natal depression among mothers; identify the causes of depression among post-natal mothers; Ànd out the association between causes of post-natal depression with demographic variable. Cases were selected by probability sampling in which total enumerative sampling technique was used; total 60 samples were selected. EPDS was used to identify the causes of post-natal depression among mothers; 39 (65%) post-natal mothers had depression not likely; 12 (20%) had possible depression; 7 (11%) had fairly high possibility of depression; 2 (3%) had probably depression. Occupations of the husband, income and marital status have high association with level of depression. The major causes of post-natal depression were Number of pregnancies, Mode of delivery, Sex of baby, Health status of baby and Planned pregnancy. It was found that all factors are signiÀcant except planned pregnancy. To conclude, psychological support would enhance the attachment between mother and children; this will further reduce the impact of depression among the mothers.
Local and Systemic Oxidative Stress Biomarkers for Male Infertility: The ORION Study

Infertility problems occur in around 10% of all couples worldwide, with male-factor infertility as the sole contributor in 20–30% of these cases. Oxidative stress (OS) is suggested to be associated with the pathophysiology of male infertility. In spermatozoa, OS can lead to damage to the cell membrane, resulting in disruption of DNA integrity and a decrease in motility. Established biomarkers for OS include free thiols and malondialdehyde (MDA), both representing different components of the reactive species interactome (RSI). This exploratory study aimed to investigate seminal plasma-free thiol and MDA levels in relation to semen parameters as defined by the World Health Organization (WHO) to determine if these markers are adequate to define local OS status. Furthermore, this study investigated if there is a relation between systemic and local OS status by comparing seminal concentrations of free thiol (R-SH, sulfhydryl groups, representing the extracellular redox status) and MDA (lipid peroxidation product) levels to those measured in serum. Free thiol and MDA measurements in both serum and semen plasma were performed in 50 males (18–55 y) of couples seeking fertility treatment. A significant positive correlation was found between seminal plasma-free thiol levels and sperm concentration and progressive motility (r = 0.383, p = 0.008 and r = 0.333, p = 0.022, respectively). In addition, a significant positive correlation was found between MDA levels in seminal plasma and sperm concentration (r = 0.314, p = 0.031). This study supports that seminal plasma-free thiols may be promising as local OS biomarkers. No associations were observed between local and systemic OS biomarker concentrations.
Fast-Growing Magnetic Wood Synthesis by an In-Situ Method

Jabon (Anthocephalus cadamba) is a fast-growing wood with low quality due to its low density and strength. The quality can be increased by modifying the wood through impregnation with various chemical compounds. In this study, jabon was impregnated with a solution of Fe and immersed in a strong base (NaOH) or a weak base (NH4OH) to form magnetite (Fe3O4) in-situ. This study analysed the use of NaOH and NH4OH in synthesising magnetic jabon wood and evaluated the wood’s characteristics. The impregnation process began with a vacuum of −0.5 bar for 0.5 h and then a pressure of 1 bar for 2 h. The samples subsequently underwent assessment of their dimensional stability, density, and characteristics. The results showed that impregnation with Fe solution followed by NaOH or NH4OH significantly affected the density and dimensional stability of the wood. The polymer weight gain was higher with NaOH, while the anti-swelling efficiency was higher with NH4OH. The density and bulking effect were increased, but the water uptake was decreased. Fourier transform infrared analysis showed the successful synthesis of magnetite. Scanning electron microscopy–energy-dispersive X-ray spectroscopy analysis revealed that magnetite covered the vessel fibre cell walls, and vibrating sample magnetometry analysis showed significant magnetic properties of the wood.
Evaluation of Machine-Learning Models for Predicting Aeolian Dust: A Case Study over the Southwestern USA

Aeolian dust has widespread consequences on health, the environment, and the hydrology over a region. This study investigated the performance of various machine-learning (ML) models including Multiple Linear Regression (MLR), Support Vector Machines (SVM), Random Forests (RF), Bayesian Regularized Neural Networks (BRNN), and Cubist (Cu) in predicting dust emissions over the Southwestern United States (US). Six meteorological and climatic variables (precipitation, air temperature, wind speed, ENSO, PDO, and NAO) were used to predict dust emissions. The correlation (r) and root mean square error (RMSE) for fine dust vary from 0.67 to 0.80, and 0.40 to 0.52 µg/m3, respectively. For coarse dust, the r and RMSE vary from 0.69 to 0.73, and 2.01 to 2.34 µg/m3, respectively. The non-linear ML models outperformed linear regression for both fine and coarse dust. ML models underestimated high concentrations of dust. Machine-learning models better predict fine dust than coarse dust over the Southwestern USA. Air temperature was found to be the most important predictor, followed by precipitation, for both fine- and coarse- dust-prediction over the region. These results improve our understanding of the predictability of Southwestern US dust.
When Friendship is Not Mutual: The Influence of Network Centrality Incongruence on Leadership Emergence and Organizational Identification

Integrating balance theory with self-perception theory, we propose that the incongruence between in-degree and out-degree centrality in a friendship network (“centrality incongruence” hereafter) contributes to the emergence of informal leadership. Through leadership emergence, centrality incongruence has a positive and indirect influence on organizational identification. In-degree centrality reflects the extent to which one is sought by others in the group as a friend, whereas out-degree centrality captures the extent to which one sees others as a friend. We surveyed 257 employees from 38 self-management business units at three observation points. Results based on polynomial regression and surface response analysis supported our hypotheses. Besides, the relationship between centrality incongruence and informal leadership emergence was stronger when the in-degree centrality is greater than the out-degree centrality compared to when the out-degree centrality is greater than the in-degree centrality. Our study points out the value of jointly considering in-degree and out-degree centrality in a social network in understanding their effects on leadership emergence and other work outcomes.
Dark current and radiation shielding studies for the ILC main linac

Electrons of dark current (DC), generated in high-gradient superconducting RF cavities (SRF) due to field emission, can be accelerated up to very high energies—19 GeV in the case of the International Linear Collider (ILC) main linac—before they are removed by focusing and steering magnets. Electromagnetic and hadron showers generated by such electrons can represent a significant radiation threat to the linac equipment and personnel. In our study, an operational scenario is analysed which is believed can be considered as the worst case scenario for the main linac regarding the DC contribution to the radiation environment in the main linac tunnel. A detailed modelling is performed for the DC electrons which are emitted from the surface of the SRF cavities and can be repeatedly accelerated in the high-gradient fields in many SRF cavities. Results of MARS15 Monte Carlo calculations, performed for the current main linac tunnel design, reveal that the prompt dose design level of 25 μSv/hr in the service tunnel can be provided by a 2.3-m thick concrete wall between the main and service ls.
Facial Emotion Recognition Using Conventional Machine Learning and Deep Learning Methods: Current Achievements, Analysis and Remaining Challenges

Facial emotion recognition (FER) is an emerging and significant research area in the pattern recognition domain. In daily life, the role of non-verbal communication is significant, and in overall communication, its involvement is around 55% to 93%. Facial emotion analysis is efficiently used in surveillance videos, expression analysis, gesture recognition, smart homes, computer games, depression treatment, patient monitoring, anxiety, detecting lies, psychoanalysis, paralinguistic communication, detecting operator fatigue and robotics. In this paper, we present a detailed review on FER. The literature is collected from different reputable research published during the current decade. This review is based on conventional machine learning (ML) and various deep learning (DL) approaches. Further, different FER datasets for evaluation metrics that are publicly available are discussed and compared with benchmark results. This paper provides a holistic review of FER using traditional ML and DL methods to highlight the future gap in this domain for new researchers. Finally, this review work is a guidebook and very helpful for young researchers in the FER area, providing a general understating and basic knowledge of the current state-of-the-art methods, and to experienced researchers looking for productive directions for future work.
Sleep Disturbances in Children with Attentional Deficit Hyperactivity Disorder and Specific Learning Disorders

Sleep disturbances may be a significant source of distress for children with neurodevelopmental disorders, and consequently also for their families. Crucially, sleep disturbances might be influenced by comorbidity. Attention deficit hyperactivity disorder (ADHD) and specific learning disorder (SLD) often co-occur, and consequently, investigating sleep disturbances in children with comorbidity of ADHD and SLD is essential. Our study aimed at detecting sleep difficulties in a group of 74 children with ADHD, 78 children with SLD, and 76 children with ADHD and SLD by using the Sleep Disturbances Scale for Children. The results showed that sleep difficulties emerge more clearly in children with comorbid ADHD and SLD compared to children with only ADHD or SLD. These sleep difficulties were not due to differences in ages and behavioral/emotional problems. In conclusion, evaluating sleep disturbances is important when assessing and managing children with ADHD, SLD, and particularly with the two comorbid conditions, to better understand their difficulties and develop tailored interventions.
Examination of students’ acceptance and usage of simulation software technology in an advanced-level merchandising class

ABSTRACT College undergraduate classes have increased the use of technological resources or tools to enhance students’ educational experiences. The simulation software technology has been used in fashion merchandising courses at US universities. Based on the technology acceptance model, the purpose of this study was to examine how students perceived usefulness, ease of use, and enjoyment of the simulation software technology and how the perceived usefulness, ease of use, and enjoyment of the technology enhanced critical thinking skills in fashion merchandising. A survey of college students at a Midwestern university in the United States was conducted. Results show that students who perceived the simulation software technology as useful, easy to use, and enjoyable were more likely to perceive improvements in critical thinking skills after use of the technology. Findings from this study may help instructors develop a ‘technology-integrated’ course and learning activity using the simulation software technology to enhance critical thinking skills in fashion merchandising.
Density effect on growth variables of eucalypt clones in a Nelder wheel experiment

Nelder’s systematic design enables studies of tree plantation spacing in relatively small areas, which is of great interest for forest planning. However, dependence between observations can arise with this method, making it difficult to use classic statistics for evaluating an experiment. Therefore, our aims were to: evaluate the relationship between dendrometric variables (tree diameter, height and volume) and the available growing area; evaluate autocorrelation among the observations; and use multivariate analysis of the profiles of the clones for comparisons of the dendrometric variables. The data are from an experiment with four Nelder wheel plots of different Eucalyptus species clones of different ages, in the state of Tocantins, Brazil. Spearman’s rank correlation was applied to evaluate the relationship between the estimates of the studied variables and respective available growing area. Autocorrelation between the observations was evaluated with Moran’s I index. To analyse the profile behaviour of the clones, three questions were proposed: (1) Are there statistical differences between the estimations made for the different clones? (2) Are there differences between treatments applied in the experiment with the clones? (3) Is there interaction between clones and spacings? The main results show that multivariate profile analysis solved the autocorrelation problem in Nelder’s systematic design. Furthermore, we obtained answers as to differences between the growth variables diameter, volume and height among the clones at different spacings, whether there is a difference between the spacings for these variables, and whether there is an interaction between clones and spacings. The analysis method used for repeated measures is appropriate to evaluate trees in Nelder wheel trials.
The Effects of Legislatively-Mandated Sobriety on First-Time and Repeat DUI Offenders in North Dakota

The 24/7 Sobriety Program is an intervention strategy mandating that impaired driving offenders remain sober as a condition of bond or pre-trial release. The goal is to monitor the most at-risk offenders in North Dakota and require that these individuals remain sober in order to keep roadways safe from hazardous drivers. As a component of the program, offenders are required to submit to twice-a-day blood alcohol concentration tests, ankle bracelet monitoring, drug patches, or urinalysis as a monitoring technique. If a program participant fails to remain sober, the individual is sent directly to jail. In 2013, House Bill 1302 – which mandated longer enrollment periods for repeat DUI offenders – went into effect. This project seeks to understand if the passing of this legislation altered behavioral performance of participants in the program. It also addresses potential deterrent effects stemming from the program. Results show that participants significantly improve crash and citation metrics after enrolling in the program. Longer sentencing periods appear to have stronger deterrent effects. Individuals who participate in the program multiple times have an above-average likelihood of relapsing into negative behavior. These individuals typically perform positively when enrolled in the program, but recidivate shortly after completing program mandates. Other programs may be more appropriate for these individuals as they represent the North Dakota driver population which likely has issues with alcohol abuse and self-control.
Platelet parameters as a diagnostic marker in early diagnosis of neonatal sepsis- Seeking newer answers for older problems

Background: Early identification and intervention of neonatal sepsis can improve the clinical outcome. Blood cultures remain the gold standard for diagnosis but are not easily available and require time. There is a need to identify and validate newer easily available cost-effective investigations, which would help in the diagnosis of neonatal sepsis. Aim: To test the hypothesis that whether platelet parameters, i.e., total platelet count (TPC), mean platelet volume (MPV), and the ratio of MPV/TPC can serve as diagnostic markers in neonatal sepsis. Methods: It is was a prospective study conducted in a tertiary care neonatal intensive care unit (NICU). The platelet parameters, i.e., TPC, MPV, and MPV/TPC of blood culture-positive septic neonates were compared with those of non-septic neonates admitted to the NICU. The diagnostic accuracy of the platelet indices was assessed by receiver operating characteristics (ROC) curves and sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Result: During the study period, 43 blood culture-positive sepsis neonates were compared with 54 cases of non-septic neonates. There was a significant difference in the mean of TPC, MPV, and MPV/TPC ratio between septic groups and non-septic groups. The sensitivity, specificity, PPV, NPV values of MPV (cut-off >9 fL) were 63.40%, 53.8%, 52.0%, and 65.11% respectively. The sensitivity, specificity, PPV, NPV of MPV/TPC ratio (>7.2) were 48.8%, 96.22%, 90.9%, and 70.42% respectively. The area under the curve (AUC) values for TPC, MPV, and MPV/TPC in the ROC analysis were 0.797, 0.641, and 0.809, respectively. Conclusion: Platelet indices MPV and MPV/TPC ratio can be useful in the early diagnosis of neonatal sepsis.
Dietary Habits and Nutritional Status among Preschool Children: An Observational Study at Bagalkot

Background: Knowing what eating habits are associated with a child's development can lead to better long-term health outcomes and improve dietary design interventions. We aimed to identify eating habits associated with the nutritional status of children between 3-6 years living in Chilapur Village of Bagalkot District. Methods: Dietary habits of preschool children were assessed with the aid of a structured score scale in an interview of mothers and fathers of preschool children. Anthropometric measurements like weight, height and mid-arm circumference have been taken to decide the nutritional status of preschool kids with help of Z rating received via WHO Anthro software. Results: Findings of the study reveals that 68% of preschool children had moderate dietary habits and 28% of them had poor eating habits and 4% of them had good eating habits. Nutritional Status assessed through anthropometric measurements shows that 39% of preschool children had moderate nutritional status according to their weight for age (≤-2 to +2 Score), 51% of preschool children had moderate nutritional status according to their height for age (≤-2 to +2 Score), and 48% of pre-school children had moderate nutritional status according to their Weight for height (≤-2 to +2 z score). A significant association was found between Dietary habits and Weight for age ( χ 2 = 8.69, p<0.05 ), Weight for height ( χ 2 = 9.12, p<0.05 ). A significant association was found between dietary habits and Family monthly income ( χ 2 = 10.58, p<0.05 ). Conclusion: Nutritional status of children aged between 3–6 years is of great health concern in India. A better nutritional diversity and meals variety and dietary styles characterized by intake of protein and calorie-rich diet seem beneficial for the growth of younger kids.
Antitranspirant Application to Sesame Plant for Salinity Stress Augmentation

A pot experiment was conducted at the green-house of the National Research Centre, Cairo. The experiment i ncluded five salinity levels o f i rrigation water (1 .5, 2 .3, 3 .12, 3 .9 and 4.7 dSm ) in number. The highest reduction was observed w hen using paraffin wax followed b y Kaolin and Ca Co treatment. Low salinity levels of 1.5 and 2.3 dSm caused an i ncrease i n pr otein ( %), while a t high salinity level -1
STUDY OF IN-PLANE SILICON NANOWIRES OBTAINED VIA A SOLID-LIQUID-SOLID GROWTH PROCESS AND THEIR SELF- ORGANIZATION FOR ELECTRONIC APPLICATIONS

This is the first Ph.D. thesis on studying the growth of in-plane silicon nanowires (SiNWs) and developing a method for self-organising them for nano-electronics applications. The growth of in-plane SiNWs is based on plasma-enhanced chemical vapour deposition (PECVD) thin film techniques and results from the interaction between a metal droplet and a hydrogenated amorphous silicon (a-Si:H) thin film. This in-plane solid-liquid-solid (IPSLS) growth mode can be considered as a reactive-spreading and moving behaviour of indium droplet on a-Si:H activated by the establishment of a surface energy gradient due to the phase transition from a-Si:H at the advancing NP edge to c-Si at the NP receding edge. In order to integrate IPSLS SiNWs in nano-electronic devices it is of prime importance to organise them in a controllable way. We propose a growth-in-place strategy which enables the SiNWs to grow along pre-patterned guiding steps. Moreover, this technique is applied to form In NPs on the sidewall of buried ITO layers, which facilitates the localization of the step-guided SiNWs. This work sets the basis for the fabrication of SiNW field effect transistors on insulator, which also allows for gate engineering and the obtaining of Fully Depleted Silicon-On-Insulator (FD-SOI).
Characterization and Evaluation of Human–Exoskeleton Interaction Dynamics: A Review

Exoskeletons and exosuits have witnessed unprecedented growth in recent years, especially in the medical and industrial sectors. In order to be successfully integrated into the current society, these devices must comply with several commercialization rules and safety standards. Due to their intrinsic coupling with human limbs, one of the main challenges is to test and prove the quality of physical interaction with humans. However, the study of physical human–exoskeleton interactions (pHEI) has been poorly addressed in the literature. Understanding and identifying the technological ways to assess pHEI is necessary for the future acceptance and large-scale use of these devices. The harmonization of these evaluation processes represents a key factor in building a still missing accepted framework to inform human–device contact safety. In this review, we identify, analyze, and discuss the metrics, testing procedures, and measurement devices used to assess pHEI in the last ten years. Furthermore, we discuss the role of pHEI in safety contact evaluation. We found a very heterogeneous panorama in terms of sensors and testing methods, which are still far from considering realistic conditions and use-cases. We identified the main gaps and drawbacks of current approaches, pointing towards a number of promising research directions. This review aspires to help the wearable robotics community find agreements on interaction quality and safety assessment testing procedures.