Miracle-dz/UniFAR-FTUs huggingface dataset:
Punishment vs. Rehabilitation: A Discourse on American Prison Reform & Comparative Analysis to Swedish Incarceration

The infrastructure of the United States prison system continues to evolve through a series of policy changes and reforms. Throughout these developments, however, the institution continues to remain rooted in the philosophy of harsh penalization. This thesis incorporates a comparative analysis between the concept of perpetrator punishment within the American federal prison system to the concept of rehabilitative justice found in the Swedish system. I conceptualize the underlying “goals” of imprisonment within the United States and Sweden and examine how they serve as an operational foundation for both institutions. I analyze American prison reform that took place during the “War on Drugs” under the Reagan administration in the 1980s, as this was a major pivotal point in modern incarceration. Using a similar timeframe to examine prison reform that occurred in Sweden, I highlight the key differences between domestic and Swedish policy. I argue that these resulting differences are symptomatic of the distinct cultural values positioned at the heart of each system. Lauren Hipplewitz POLS 4997W December 10, 2020 Final Draft of Thesis Advisor: Dr. Kristin Kelly
Optimally Generalized Regularization Methods for Solving Linear Inverse Problems

In order to solve ill-posed linear inverse problems, we modify the Tikhonov regularization method by proposing three different preconditioners, such that the resultant linear systems are equivalent to the original one, without drop- ping out the regularized term on the right-hand side. As a consequence, the new regularization methods can retain both the regularization effect and the accuracy of solution. The preconditioned coefficient matrix is arranged to be equilibrated or diagonally dominated to derive the optimal scales in the introduced precondi- tioning matrix. Then we apply the iterative scheme to find the solution of ill-posed linear inverse problem. Two theorems are proved that the iterative sequences are monotonically convergent to the true solution. The presently proposed optimally generalized regularization methods are able to overcome the ill-posedness of linear inverse problems, and provide rather accurate numerical solution.
Effects of an acute swimming session until exhaustion in myocytes isolated from Wistar rats

The role of regular physical exercise is recognized for the prevention, control and treatment of cardiovascular diseases. However, studies show that after strenuous aerobic exercise sessions in healthy individuals can lead to cardiac damage, due to the high degree of stress imposed on myocardial structures. This study verifies the effects of swimming to exhaustion on contraction and relaxation velocities, as well as the velocity of calcium release and reuptake in cardiomyocytes isolated from the left ventricle. Wistar animals aged 16 weeks were submitted to a protocol of swimming until exhaustion with a load of 5% of body weight and later the cardiomyocytes were isolated. It was observed that an acute session of swimming until exhaustion promoted an increase in the velocity of contraction and relaxation and an increase in the velocity of calcium release. Exercise to exhaustion promotes adverse effects on the myocardium, however more studies are needed to explain these effects and demonstrate the molecular mechanisms involved in the process.
Enhanced Electrical Transport and Photoconductivity of ZnO/ZnS Core/Shell Nanowires Based on Piezotronic and Piezo-Phototronic Effects

We report a significant enhancement in the electrical transport and photoconductivity of ZnO/ZnS core/shell nanowires (NWs) compared to those of ZnO NWs via the application of compressive strain. Under a compressive strain of −0.15%, the output current of the ZnO/ZnS core/shell NWs increases by 91.1% compared to that under the no-strain condition, whereas that of the ZnO NWs under the same condition is 42.7%. The significant increase in the output current of the ZnO/ZnS core/shell NWs is attributed to the type-II band alignment and strain-induced piezopotential changes at the junction interface, which induce a reduction in the barrier height to enable efficient charge carrier transport. Furthermore, under UV illumination and a compressive strain of −0.15%, although the photocurrent of the ZnO/ZnS core/shell NWs increases by 4.5 times compared to that of the ZnO NWs, the relative increase in the photocurrent of the ZnO/ZnS core/shell NWs is 11.7% compared to that under the no-strain condition, while the photocurrent of the ZnO NWs increases by 32.3% under the same condition. A decrease in the increase rate in the photocurrent of the ZnO/ZnS core/shell NWs with a change in strain under UV light compared to that under the dark condition can be explained by the piezoelectric screening effect induced by photogenerated carriers. By calculating the change in the Schottky barrier height (SBH), we demonstrate that the piezoelectric potential with a change in strain decreased the SBH, thus increasing the current level. Lastly, we propose a mechanism of the piezotronic and piezo-phototronic effects under applied strain and their effects on energy-band diagrams.
Integration of point-of-care screening for type 2 diabetes mellitus and hypertension with COVID-19 rapid antigen screening in Johannesburg, South Africa

Aims We sought to evaluate the yield and linkage-to-care for diabetes and hypertension screening alongside a study assessing the use of rapid antigen tests for COVID-19 in taxi ranks in Johannesburg, South Africa. Methods Participants were recruited from Germiston taxi rank. We recorded results of blood glucose (BG), blood pressure (BP), waist circumference, smoking status, height, and weight. Participants who had elevated BG (fasting ≥7.0; random ≥11.1mmol/L) and/or BP (diastolic ≥90 and systolic ≥140mmHg) were referred to their clinic and phoned to confirm linkage. Results 1169 participants were enrolled and screened for elevated BG and elevated BP. Combining participants with a previous diagnosis of diabetes (n = 23, 2.0%; 95% CI:1.3–2.9%) and those that had an elevated BG measurement (n = 60, 5.2%; 95% CI:4.1–6.6%) at study enrollment, we estimated an overall indicative prevalence of diabetes of 7.1% (95% CI:5.7–8.7%). When combining those with known hypertension at study enrollment (n = 124, 10.6%; 95% CI:8.9–12.5%) and those with elevated BP (n = 202; 17.3%; 95% CI:15.2–19.5%), we get an overall prevalence of hypertension of 27.9% (95% CI:25.4–30.1%). Only 30.0% of those with elevated BG and 16.3% of those with elevated BP linked-to-care. Conclusion By opportunistically leveraging existing COVID-19 screening in South Africa to screen for diabetes and hypertension, 22% of participants received a potential new diagnosis. We had poor linkage-to-care following screening. Future research should evaluate options for improving linkage-to-care, and evaluate the large-scale feasibility of this simple screening tool.
Testing the job demands-resources model for organizational commitment among Indian correctional officers

ABSTRACT Correctional institutions are manpower-intensive organizations, and organizational commitment is important for their successful functioning. This study uses the job demands model to examine effect of workplace variables on organizational commitment. Using a sample of 163 correctional officers from a prison in Haryana State, India, we find that job demands (fear of being hurt and work and role overload) have no significant effect of organizational commitment. All four components of job resources (instrumental communication, job autonomy, quality of supervision, and job variety) were found to be positively and significantly associated with organizational commitment. The study highlights the importance of adequate knowledge of job resources in trying to raise the affective commitment of correctional officers.
Rate of Obstetrical Complications and Medical Interventions in Low-Risk Patients: A Cohort Study in Dakar, Senegal

Background: “Low-risk” pregnancy is defined as a pregnancy that develops physiologically in a healthy woman and remains healthy. In practice, “low-risk” pregnancies are defined by excluding high-risk pregnancies. Objectives: Eva-luate the rate of complications and medical interventions in “low-risk” pregnant women. Methods: This was a retrospective cohort study assessing the risk of obstetrical complications and medical interventions in low-risk patients from January 2010 to December 2020 at Philippe Maguilen Senghor Health Center in Dakar, Senegal. Results: There were 10,979 low-risk patients out of a total of 52,768, accounting for 20.8%. As medical interventions, episiotomy was performed in 27.5% and cesarean section in 8.7%. Acute fetal distress was observed in 4.1%. A low Apgar score at the fifth minute was observed in 1.89% (whereas it was 3.49% in high risk patients). Newborn-resuscitation was performed in 10.7%. Neonatal mortality was 5‰. Conclusion: Low-risk pregnancies are not without “risk”, and thus care-givers should prepare for risks even at dealing with low risk patients.
SPP1/AnxA1/TIMP1 as Essential Genes Regulate the Inflammatory Response in the Acute Phase of Cerebral Ischemia-Reperfusion in Rats

Background Ischemic injury in stroke is followed by extensive neurovascular inflammation and changes in ischemic penumbra gene expression patterns. However, the key molecules involved in the inflammatory response during the acute phase of ischemic stroke remain unclear. Methods Gene expression profiles of two rat ischemic stroke-related data sets, GSE61616 and GSE97537, were downloaded from the GEO database for Gene Set Enrichment Analysis (GSEA). Then, GEO2R was used to screen differentially expressed genes (DEGs). Furthermore, 170 differentially expressed intersection genes were screened and analyzed for Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Candidate genes and miRNAs were obtained by DAVID, Metascape, Cytoscape, STRING, and TargetScan. Finally, the rat middle cerebral artery occlusion-reperfusion (MCAO/R) model was constructed, and qRT-PCR was used to verify the predicted potential miRNA molecule and its target genes. Results GO and KEGG analyses showed that 170 genes were highly associated with inflammatory cell activation and cytokine production. After cluster analysis, seven hub genes highly correlated with post-stroke neuroinflammation were obtained: Cxcl1, Kng1, Il6, AnxA1, TIMP1, SPP1, and Ccl6. The results of TargetScan further suggested that miR-340-5p may negatively regulate SPP1, AnxA1, and TIMP1 simultaneously. In the ischemic penumbra of rats 24 h after MCAO/R, the level of miR-340-5p significantly decreased compared with the control group, while the concentration of SPP1, AnxA1, and TIMP1 increased. Time-course studies demonstrated that the mRNA expression levels of SPP1, AnxA1, and TIMP1 fluctuated dramatically throughout the acute phase of cerebral ischemia-reperfusion (I/R). Conclusion Our study suggests that differentially expressed genes SPP1, TIMP1, and ANXA1 may play a vital role in the inflammatory response during the acute phase of cerebral ischemia-reperfusion injury. These genes may be negatively regulated by miR-340-5p. Our results may provide new insights into the complex pathophysiological mechanisms of secondary inflammation after stroke.
Vibration‐based structural health monitoring exploiting a combination of convolutional neural networks and autoencoders for temperature effects neutralization

Damage diagnosis in the structural field (mechanical, civil, aerospace, etc.) is a topic of active development and research. In recent years, considerable enhancements in this field have been achieved mainly due to advances in sensor technologies, the evolution of signal processing algorithms, and the increase of computational power. As one of the main consequences, the amount of data recorded from the sensorial equipment has steadily grown in quantity and complexity. In addition to that, these data are almost always significantly affected by many factors, which are not only related to the presence of damages but, for instance, also to the environmental and operative conditions under which the structural system is working. In order to handle these challenges, in the last few years, new deep learning models have been proposed, based on deep and heterogeneous architectures, able to deal with big data, also containing intricate diagnostic features that are difficult to be extracted. With this aim, this paper proposes a new vibration‐based structural diagnosis tool that exploits the power of convolutional neural networks (CNNs) to extract subtle damage‐related features from complex transmissibility function (TF) spectra even in presence of potentially confounding temperature variations. The diagnostic algorithm stems from the coupling of a CNN with an unsupervised anomaly detection algorithm based on autoencoders (AEs) to neutralize the effects of temperature variations and increase the damage diagnosis accuracy. The proposed approach is demonstrated with reference to a simple, but realistic, numerical case study of a structural beam subjected to temperature changes.
Exploration of the Role of Relationships and Virtual Learning on Academic Performance and Mental Health

Background The coronavirus disease 2019 (COVID-19) pandemic caused medical schools to rapidly transition to online/distance learning. Online learning is often associated with poor academic performance, mental health, and student-to-faculty relationships. The purpose of this study is to determine if correlations exist between academic performance, mental health, study location, and student/faculty relationships among medical students. Methodology First-year medical students received a survey asking them to reflect on their study location, mental health, and student/faculty relationships during the COVID-19 pandemic. Second- and third-year medical students received a similar survey asking them to reflect on their experiences from the perspective of their first year of medical school (pre-pandemic). The first five exam scores were gathered for all participants. Pearson’s correlation coefficient was calculated between all variables. Results Academic performance was found to be positively correlated with both mental health (R = 0.215, p = 0.016) and relationships among students (R = 0.0259, p = 0.004), while negatively correlated with the percentage of time spent studying at home (R = -0.185, p = 0.039). Mental health was additionally found to be positively correlated with relationships to faculty (R = 0.230, p = 0.01) and relationships to students (R = 0.245, p = 0.006). Conclusions Academic performance and mental health are correlated with relationships and study location. These correlations may explain the negative outcomes associated with online learning in medical education.
Dynamics of condensation in zero-range processes

The dynamics of a class of zero-range processes exhibiting a condensation transition in the stationary state is studied. The system evolves in time starting from a random disordered initial condition. The analytical study of the large-time behaviour of the system in its mean-field geometry provides a guide for the numerical study of the one-dimensional version of the model. Most qualitative features of the mean-field case are still present in the one-dimensional system, both in the condensed phase and at criticality. In particular the scaling analysis, valid for the mean-field system at large time and for large values of the site occupancy, still holds in one dimension. The dynamical exponent z, characteristic of the growth of the condensate, is changed from its mean-field value 2 to 3. In the presence of a bias, the mean-field value z = 2 is recovered. The dynamical exponent zc, characteristic of the growth of critical fluctuations, is changed from its mean-field value 2 to a larger value, zc 5. In the presence of a bias, zc 3.
Effective Connectivity in Spinal Cord Injury-Induced Neuropathic Pain

Aim: The aim of this study was to differentiate the effects of spinal cord injury (SCI) and central neuropathic pain (CNP) on effective connectivity during motor imagery of legs, where CNP is typically experienced. Methods: Multichannel EEG was recorded during motor imagery of the legs in 3 groups of people: able-bodied (N = 10), SCI with existing CNP (N = 10), and SCI with no CNP (N = 20). The last group was followed up for 6 months to check for the onset of CNP. Source reconstruction was performed to obtain cortical activity in 17 areas spanning sensorimotor regions and pain matrix. Effective connectivity was calculated using the directed transfer function in 4 frequency bands and compared between groups. Results: A total of 50% of the SCI group with no CNP developed CNP later. Statistically significant differences in effective connectivity were found between all groups. The differences between groups were not dependent on the frequency band. Outflows from the supplementary motor area were greater for the able-bodied group while the outflows from the secondary somatosensory cortex were greater for the SCI groups. The group with existing CNP showed the least differences from the able-bodied group, appearing to reverse the effects of SCI. The connectivities involving the pain matrix were different between able-bodied and SCI groups irrespective of CNP status, indicating their involvement in motor networks generally. Significance: The study findings might help guide therapeutic interventions targeted at the brain for CNP alleviation as well as motor recovery post SCI.
Analysis of Skin disease techniques using Smart Phone and Digital Camera Identification of Skin Disease

Skin diseases are a serious health issue that affects a large number of individuals. In recent years, with the fast advancement of technology and the use of various data mining approaches, dermatological predictive classification has become increasingly predictive and accurate. It is more help to dermatologist to identify the disease, As a result, the development of machine learning approaches capable of efficiently. The purpose of this study is making an application of identification skin disease images by using the machines learning method, Support Vector Machine (SVM), and KNN techniques. The image processes and machine learning is performed early detection of skin diseases. The aim of this study is determined the classification of skin diseases in humans. Each skin disease has symptoms. It has five skin diseases such as Acne, Psoriasis, Wrath, Psoriasis, and Ulcer. We have collected 314 skin disease images from the government of hospital, Aurangabad with the help of mobile camera and Sony HD camera. Gaussian Filter is used for image pre-processing. The segmentation method is used for K-Means Clustering and the feature extraction method are used for feature extraction. We have used Haar feature, color feature, FCM, OS-FCM, GLCM and LBF features for classifications. Based on the result, the SVM is given 92% accuracy for haar feature, FCM and OS-FCM. and KNN classifier, K-Means are given 89% and 89% accuracy using mobile phone camera dataset. The SVM, KNN and K-Means are given 91%, 87% and 89% accuracy respectively using Sony HD camera dataset. SVM is given good result in both dataset.
Customers facing companies’ content personalisation attempts: paradoxical tensions, strategies and managerial insights

ABSTRACT Personalisation enables companies to learn from their customers’ online data and to adapt their content accordingly. However, although customers may value personalisation, they may also have negative perceptions of it. The literature identifies these contradictory but interrelated perceptions as a paradox. This qualitative research investigates the process underlying the triggering and management of the paradoxical tensions of personalisation. In light of paradox theory, our contributions are threefold. First, we identify the different paradoxes that personalisation triggers and their triggering mechanism. Second, we emphasise how customers manage these tensions by adopting resolution and acceptance strategies. Third, we identify the levers that companies can use to mitigate these paradoxical tensions.
Factors that affect lip changes following incisor retraction in Vietnamese adults with a convex facial profile

OBJECTIVE: This study aimed to evaluate the factors that influence lip change through the results of tooth anterior retraction by fixed orthodontic treatment in Vietnamese adult patients with a convex facial profile. MATERIALS AND METHODS: This prospective study included 32 Vietnamese adults who have convex facial profiles. Digital software measurements according to Arnett's analysis and the superimposition method were performed to evaluate the changes in dentoskeletal structures, and soft tissue variables included lip change. A multiple logistic regression model was applied with various explanatory variables to analyze the correlation. RESULTS: The study revealed a strong correlation of lip change at the site of the cervical point and incisal edge of the upper incisors, and the cervical position demonstrated a stronger correlation. The ratio between lip change and incisor retraction in patients is approximately 1:2.3 at the incisal edge and 1:1.3 at the cervical point. CONCLUSION: Lip change was associated with incisor retraction at the cervical and incisal edge, but it did not correlate with the rotation axis of the upper incisors.
Understanding the aging mechanism of calcium silicate hydrates under the action of solar radiation

Abstract This work examines the influencing mechanism of light radiation on performances and structures of calcium silicate hydrates (C-S-H) through exposing synthetic C-S-H samples to high-power Xenon radiation. The compositions, chemical structures and nanomorphology of C-S-H were investigated using XRD, TG, 29Si NMR, Ca XANES, Si XANES and TEM. Xenon radiation reduces the chemically bound water content in C-S-H and the drying effect induced by Xenon radiation is more pronounced in C-S-H with lower Ca/Si ratio. Xenon radiation increases the polymerization of C-S-H and elongates the silicate chain by driving separated Si–O tetrahedron to connect with each other without changing its Ca/Si ratio. Furthermore, Xenon radiation reduces the coordination numbers of Ca–O and causes the self-organization of chemical structure at molecular and atomic scales. The existence of portlandite improves the resistance of C-S-H to compositional and structural changes induced by Xenon radiation. These findings pave the way for understanding aging mechanism of cement-based materials under the action of solar radiation. Graphic Abstract
PRMT1, a Key Modulator of Unliganded Progesterone Receptor Signaling in Breast Cancer

The progesterone receptor (PR) is a key player in major physiological and pathological responses in women, and the signaling pathways triggered following hormone binding have been extensively studied, particularly with respect to breast cancer development and progression. Interestingly, growing evidence suggests a fundamental role for PR on breast cancer cell homeostasis in hormone-depleted conditions, with hormone-free or unliganded PR (uPR) involved in the silencing of relevant genes prior to hormonal stimulation. We herein identify the protein arginine methyltransferase PRMT1 as a novel actor in uPR signaling. In unstimulated T47D breast cancer cells, PRMT1 interacts and functions alongside uPR and its partners to target endogenous progesterone-responsive promoters. PRMT1 helps to finely tune the silencing of responsive genes, likely by promoting a proper BRCA1-mediated degradation and turnover of unliganded PR. As such, PRMT1 emerges as a key transcriptional coregulator of PR for a subset of relevant progestin-dependent genes before hormonal treatment. Since women experience periods of hormonal fluctuation throughout their lifetime, understanding how steroid receptor pathways in breast cancer cells are regulated when hormones decline may help to determine how to override treatment failure to hormonal therapy and improve patient outcome.