Miracle-dz/UniFAR-FTUs huggingface dataset:
C H A P T E R THIRTEEN An Ethical Enquiry that Questions whether Psychiatrists truly are Mental Health/Disability Experts? Reasons to Doubt!

A crisis of confidence regarding Psychiatry exists even among psychiatrists themselves. Psychiatry has a checkered history and its alliance with the pharmaceutical industry, aka Big-Pharma, continues to reinforce a need for healthy skepticism. Fundamentally there is an over-reliance on the questionable expertise and authority afforded psychiatrists as the specialists of mental health. I contend that the authority of psychiatry is misplaced and too often, harmful. Since the criteria required to justify and satisfy psychiatric expertise is not fully established as can be substantiated by compelling reasons to rethink its authority as a reliable profession in its current form. Psychiatric expertise is not particularly scientific and this is especially dangerous in a sector that prescribes psychoactive drugs. There are a number of identified criteria that would otherwise substantiate psychiatric expertise and whilst partially existent, are nonetheless deficient. These major yet deficient aspects of psychiatric practice concern diagnostic problems – reliability and verification of diagnoses and accurate testable validity of diagnoses - mainly due to an absence of identifiable underlying biomarkers ordinarily related to disease or biological conditions. Psychiatrists often fail to distinguish between reactive-depression (reaction to external event or circumstance) and endogenous-depression (biological) resulting, in part, from incorrectly distinguishing between conditions constitutive of ‘trait’ (endogenous) and of those of ‘state’ (e.g. reactive depression; adverse effects from medication, etc.).
Environmental Economy and Policy Research Discussion Paper

In this paper we employ the choice experiment method to estimate residents’ willingness to pay (WTP) for improvements in the solid waste management (SWM) services provided in Chandernagore and South Dum Dum municipalities of Greater Kolkata in West Bengal, India. 101 randomly selected residents took part in a choice experiment survey. Data are analysed with conditional logit, random parameter logit and random parameter logit with interactions models. The best fitting random parameter logit with interactions model reveal that there is significant conditional and unconditional heterogeneity in residents’ preferences for improvements in SWM services. The results reveal that on average residents of these municipalities are WTP significant amounts, in terms of higher monthly municipality taxes, to increase the frequency of waste collection, and to ensure that the waste is collected by covered trucks. Differences in WTP values across residents, however, should be taken into consideration to ensure social equity. The results reported in this paper have important policy implications for informing efficient, effective and equitable SWM services aimed at reducing local environmental pollution and the consequent public health risks.
Analysis of Implant Survival Placed in Resorbed Alveolar Ridges Regenerated with Iliac Crest Autogenous Grafts: A 15-Year Follow-Up

Background: Over the years, techniques have been developed that allow bone to be placed where it is deficient, in order to regenerate the area of interest, and one of these involves the insertion of a graft. The iliac crest is one of the most frequently used donor sites in the context of extra-oral autologous blood harvesting, as it allows for the harvesting of a large quantity of both cortical and corticomedullary bone as well as spongiosa alone. Methods: The retrospective study aims to evaluate the implant survival 15 years after a definitive prosthetic rehabilitation on implants, inserted as a result of an autologous bone graft taken from the iliac crest. The 72 implants examined were positioned in two surgical stages in the two upper and lower maxillary arches, some with the classic implant surgical technique and others with a guided implant surgical technique. Controls were performed with radiological examination, in particular orthopantomography, and clinical evaluation. Result: Of the 72 implants placed, none showed implant failure 1 year after placement. At 5 years the success rate is 98.6%, at 10 years it is 94.4% and at 15 years it is 86.1%. The results show a total of 10 implants were lost: 1 at 5 years, 3 at 10 years and 6 at 15 years. Conclusion: Despite the difficulties related to post-operative morbidity and the need for a second operation, the iliac crest graft allows the rehabilitation of large edentulous areas, with a reduced percentage of resorption and ensures faster neoangiogenesis with faster engraftment.
Genetic Influences on Brain Gene Expression in Rats Selected for Tameness and Aggression

Interindividual differences in many behaviors are partly due to genetic differences, but the identi ﬁ cation of the genes and variants that in ﬂ uence behavior remains challenging. Here, we studied an F 2 intercross of two outbred lines of rats selected for tame and aggressive behavior toward humans for . 64 generations. By using a mapping approach that is able to identify genetic loci segregating within the lines, we identi ﬁ ed four times more loci in ﬂ uencing tameness and aggression than by an approach that assumes ﬁ xation of causative alleles, suggesting that many causative loci were not driven to ﬁ xation by the selection. We used RNA sequencing in 150 F 2 animals to identify hundreds of loci that in ﬂ uence brain gene expression. Several of these loci colocalize with tameness loci and may re ﬂ ect the same genetic variants. Through analyses of correlations between allele effects on behavior and gene expression, differential expression between the tame and aggressive rat selection lines, and correlations between gene expression and tameness in F 2 animals, we identify the genes Gltscr2 , Lgi4 , Zfp40
VU Research Portal Reinforcement Learning with Option Machines

Reinforcement learning (RL) is a powerful framework for learning complex behaviors, but lacks adoption in many settings due to sample size requirements. We introduce a framework for increasing sample efficiency of RL algorithms. Our approach focuses on optimizing environment re-wards with high-level instructions. These are modeled as a high-level controller over temporally extended actions known as options . These options can be looped, interleaved and partially ordered with a rich language for high-level instructions. Cru-cially, the instructions may be underspecified in the sense that following them does not guarantee high reward in the environment. We present an algo-rithm for control with these so-called option machines (OMs), discuss option selection for the partially ordered case and describe an algorithm for learning with OMs. We compare our approach in zero-shot, single-and multi-task settings in an environment with fully specified and underspecified instructions. We find that OMs perform significantly better than or comparable to the state-of-art in all environments and learning settings.
Effects of a Control Release Nitrogen Fertilizer and Thinning on the Nitrogen Dynamics of a Mid-Rotation Loblolly Pine Stand in the Piedmont of Virginia

Nitrogen deficiency is characteristic of many mid-rotation loblolly pine (Pinus taeda L.) plantations in the Piedmont region of the southeastern USA. Fertilization with urea is the most common method used to correct this deficiency. Previous studies show that urea fertilization produces a rapid pulse of available nitrogen (N) with only a portion being utilized by plantation trees. Controlled release fertilizers release available N more slowly over a longer period of time and therefore may result in greater uptake efficiency. The objective of this study was to compare Nitroform®, a urea-formaldehyde controlled release N fertilizer versus urea and a control by measuring the effects of the two fertilizer treatments on N availability and loss as: total KCl extractable-N, total ion exchange membrane-N (IEM-N), N mineralization, and N volatilization, in a mid-rotation loblolly pine plantation in the Piedmont of Virginia. In addition, mid-summer and mid-winter fertilizations were compared to assess fertilizer uptake as a function of season. After the summer fertilization, Nitroform® significantly increased total KCl-extractable N, IEM-N, and N mineralization for two to three months over urea and the control. Three hundred times more N volatilized from urea than from controlled release Nitroform®. Interestingly, seven months after the summer application, the controlled release Nitroform® showed marked immobilization for three months while urea demonstrated greater N mineralization. After the winter application, fertilization with urea demonstrated greater soil inorganic N concentrations for two to three
The Role of Political Parties Under Deliberative Democracy in China

The paper investigates the function of political parties in China's system of deliberative democracy. Deliberative democracy places a strong emphasis on inclusive decision-making procedures and engaged citizens. It offers insight on the contributions, difficulties, and possibilities encountered by political parties in fostering discourse and encouraging public involvement by evaluating their participation in local deliberative forums and legislative debate. The paper aims to shed light on the political parties' role in China's deliberative democracy by closely examining their contributions to the inclusive discussion, public involvement, and democratic decision-making processes. The paper uses secondary data and were analyzed thematically. The results emphasize the value of openness, responsibility, diversity, and internal party democracy. Political parties must develop these facets inside themselves if they are to play a greater role in encouraging good governance and civic engagement. It advances knowledge of political party dynamics and their possibilities within China's developing deliberative democracy framework
Edinburgh Research Explorer A dutch treatment of an elitist approach to articulatory-acoustic feature classification

A novel approach to articulatory-acoustic feature extraction has been developed for enhancing the accuracy of classification associated with place and manner of articulation information. This “elitist” approach is tested on a corpus of spontaneous Dutch using two different systems, one trained on a subset of the same corpus, the other trained on a corpus from a different language (American English). The feature dimensions, voicing and manner of articulation transfer relatively well between the two languages. However, place information transfers less well. Manner-specific training can be used to improve classification of articulatory place information.
After Daewoo? Current status and perspectives of large-scale land acquisition in Madagascar

On March 17, 2009, the fall of the Ravalomanana government in Madagascar resounded in the national and international media. The event assumed a unique character, as land questions appeared to be among the claims that led to the uprising. Accusations of "selling off the ancestors' land" were brought against President Ravalomanana following the revelation of a project to lease more than one million hectares of agricultural land, under obscure conditions, to a South Korean company, Daewoo Logistics. Since the beginning of the 2000s, a number of land acquisition projects in the agricultural sector have been announced or revealed by the press. The little information available implied that they were aimed at the production of food commodities, agrofuels, or wood. The land areas in question comprised between 1,000 and 200,000 hectares per invest-ment project. This study presents the evolution of large agricultural investments in Madagascar between 2005 and 2010. Commissioned by the International Land Coalition (ILC), it was realized by the Malagasy Land Observatory (l'Observatoire du Foncier a Madagascar) and CIRAD. Its aims are to: Examine the establishment processes of the Daewoo and Varun projects, both of which were eventually abandoned; Describe the status of land investment projects, by differentiating between those that have simply been announced and those that are effectively underway; Determine the operators' objectives with regards to land acquisition and to pinpoint the status of their applications for land; Examine the legal framework that is meant to regulate these investments; Analyze operators' practices in accessing land as well as the means of regulation, both formal and informal, of these investments at the local and national levels; Raise core questions to be addressed in the framework of a future debate on the role of these investments in the agricultural sector and on the institutional mechanisms that need to be reinforced in order to improve the transparency of land acquisition projects, to clarify the procedures for investors to follow, and to limit negative social, economic, and environmental impacts. (Resume d'auteur)
ADDITIVE MANUFACTURING OF SPARE PARTS FOR SPECIAL VEHICLES IN THE OIL AND GAS INDUSTRY

At oil and gas production facilities and other industries, special transport and technological machines of foreign production are often used. One of the tasks of the technical department of organizations is to provide cars with spare parts and consumables. Many spare parts may not be manufactured in a particular country. In this regard, a rather long supply chain of spare parts with a large number of intermediate links is being formed. This increases the delivery time and the already high cost of spare parts. The article proposes a solution to the problems of long terms and cost of supplying spare parts by introducing additive manufacturing technologies for spare parts in organizations that manage the fleet of vehicles.
Factors of geographical variability of antimicrobial use in Japan

Background The evidence regarding the factors affecting the geographical variation of antimicrobial use (AMU) is relatively scarce. The study aimed to evaluate factors potentially associated with geographical variability of AMU per day per 1,000 habitants in 47 prefectures of Japan. Methods This is an observational ecological study using the Japanese national database in 2019. The outcome was the de�ned daily doses per 1,000 inhabitants per day by prefecture. The multivariable negative binomial regression analysis was conducted using patient-and physician-level variables. Results The study included 605,391,054 de�ned daily doses of AMU in 2019 from the 47 prefectures. In the multivariable negative binomial regression analyses for the outcome of total AMU, the proportion of females (RR 1.04 [1.01 − 1.08] per 1% increase, p = 0.021), the proportion of upper secondary graduates going to further education (RR 1.01 [1.00 − 1.01] per 1% increase, p = 0.005) and the annual number of diagnoses related with upper respiratory infections (URIs) per 1,000 inhabitants per day (RR 1.21 [1.10 − 1.34], p < 0.001) were signi�cantly correlated with total AMU.
A Deep Learning Approach for Automatic Segmentation during Daily MRI-Linac Radiotherapy of Glioblastoma

Simple Summary Current auto-segmentation methods for glioblastoma utilize mainly pre-operative 1.5T and 3T MRI. The first commercial MRI-linear accelerator (linac) radiation treatment platform acquires low-field (0.35T) post-operative MRI at the delivery of each treatment. This study presents the first automatic brain lesion segmentation network developed for MRI-linac to track tumor changes during radiotherapy. The tumors and resection cavities are automatically segmented using a deep learning network, allowing for daily monitoring of tumor volume changes, creation of tools necessary for adaptive radiotherapy of glioblastoma, and providing MRI regions of interest for further analyses that may discover prognostic markers. Abstract Glioblastoma changes during chemoradiotherapy are inferred from high-field MRI before and after treatment but are rarely investigated during radiotherapy. The purpose of this study was to develop a deep learning network to automatically segment glioblastoma tumors on daily treatment set-up scans from the first glioblastoma patients treated on MRI-linac. Glioblastoma patients were prospectively imaged daily during chemoradiotherapy on 0.35T MRI-linac. Tumor and edema (tumor lesion) and resection cavity kinetics throughout the treatment were manually segmented on these daily MRI. Utilizing a convolutional neural network, an automatic segmentation deep learning network was built. A nine-fold cross-validation schema was used to train the network using 80:10:10 for training, validation, and testing. Thirty-six glioblastoma patients were imaged pre-treatment and 30 times during radiotherapy (n = 31 volumes, total of 930 MRIs). The average tumor lesion and resection cavity volumes were 94.56 ± 64.68 cc and 72.44 ± 35.08 cc, respectively. The average Dice similarity coefficient between manual and auto-segmentation for tumor lesion and resection cavity across all patients was 0.67 and 0.84, respectively. This is the first brain lesion segmentation network developed for MRI-linac. The network performed comparably to the only other published network for auto-segmentation of post-operative glioblastoma lesions. Segmented volumes can be utilized for adaptive radiotherapy and propagated across multiple MRI contrasts to create a prognostic model for glioblastoma based on multiparametric MRI.
Effectiveness of different types of traps of different heights against fruit flies (Bactrocera spp.) on guava plants (Psidium guajava L.)

Fruit fly (Bactrocera spp.) is one of the main pest of guava so its presence needs to be controlled because it causes production to decrase up to 50%. Various control efforts can be caried out, including the use of color and scent traps. This research was carried out in Sei Mencirim Village February-April 2022. The method used a randomize group with 2 factors and 3 test, the first factor is the type of trap with 5 levels, namely control, yellow color trap, green color trap, guava fruit waste extract, and guava fruit flesh waste and the second factor is the height of the trap with 3 levels, namely trap heights of 1 m, 1.5 m, and 2 m. The result showed the number of imago populations of trapped fruit flies and heighest number of trapped male fruit flies in the green color type, for the heighest number of trapped female fruit flies in yellow color traps. At a trap height of 1.5 m, the number of fruit fly imago populations was shown and the highest number of fruit fly imago populations was shown and the heighest number of male and female fruit flies trapped.
A Uniﬁed Sense Inventory for Word Sense Disambiguation in Polish

We introduce a comprehensive evaluation benchmark for Polish Word Sense Disambiguation task. The benchmark consists of 7 distinct datasets with sense annotations based on plWordNet –4.2. As far as we know, our work is a ﬁrst attempt to standardise existing sense annotated data for Polish. We also follow the recent trends of neural WSD solutions and we test transfer learning models, as well as hybrid architectures combining lexico-semantic networks with neural text encoders. Finally, we investigate the impact of bilingual training on WSD performance. The bilingual model obtains new State of the Art performance in Polish WSD task.
Explainable Machine Learning with Pairwise Interactions for Predicting Conversion from Mild Cognitive Impairment to Alzheimer’s Disease Utilizing Multi-Modalities Data

Background: Predicting cognition decline in patients with mild cognitive impairment (MCI) is crucial for identifying high-risk individuals and implementing effective management. To improve predicting MCI-to-AD conversion, it is necessary to consider various factors using explainable machine learning (XAI) models which provide interpretability while maintaining predictive accuracy. This study used the Explainable Boosting Machine (EBM) model with multimodal features to predict the conversion of MCI to AD during different follow-up periods while providing interpretability. Methods: This retrospective case-control study is conducted with data obtained from the ADNI database, with records of 1042 MCI patients from 2006 to 2022 included. The exposures included in this study were MRI biomarkers, cognitive scores, demographics, and clinical features. The main outcome was AD conversion from aMCI during follow-up. The EBM model was utilized to predict aMCI converting to AD based on three feature combinations, obtaining interpretability while ensuring accuracy. Meanwhile, the interaction effect was considered in the model. The three feature combinations were compared in different follow-up periods with accuracy, sensitivity, specificity, and AUC-ROC. The global and local explanations are displayed by importance ranking and feature interpretability plots. Results: The five-years prediction accuracy reached 85% (AUC = 0.92) using both cognitive scores and MRI markers. Apart from accuracies, we obtained features’ importance in different follow-up periods. In early stage of AD, the MRI markers play a major role, while for middle-term, the cognitive scores are more important. Feature risk scoring plots demonstrated insightful nonlinear interactive associations between selected factors and outcome. In one-year prediction, lower right inferior temporal volume (<9000) is significantly associated with AD conversion. For two-year prediction, low left inferior temporal thickness (<2) is most critical. For three-year prediction, higher FAQ scores (>4) is the most important. During four-year prediction, APOE4 is the most critical. For five-year prediction, lower right entorhinal volume (<1000) is the most critical feature. Conclusions: The established glass-box model EBMs with multimodal features demonstrated a superior ability with detailed interpretability in predicting AD conversion from MCI. Multi features with significant importance were identified. Further study may be of significance to determine whether the established prediction tool would improve clinical management for AD patients.
Systematic review and meta-analysis of verbal and physical violence against healthcare workers in the Eastern Mediterranean Region.

Background Workplace violence is a serious threat to healthcare workers worldwide. Aim We aimed to determine the prevalence of physical and verbal violence against healthcare workers in the WHO Eastern Mediterranean Region and Türkiye. Methods We searched the Medline (via PubMed), Cochrane Library, Scopus, Science Direct, Web of Science and ProQuest databases along with reference lists from selected articles. Studies of health workers exposed to verbal and/or physical violence by patients or their relatives conducted in the WHO Eastern Mediterranean Region and Türkiye among staff working in hospitals and primary health care services were included. Seventy-five of the 3513 articles identified of studies conducted during 1999-2021 were eligible. The data were analysed using MetaXL version 5.3 and STATA version 16. Results This study covered 69 024 healthcare workers from 22 countries. Meta-analysis showed that 63.0% (95% CI: 46.7- 79.2) of them had experienced verbal violence and 17.0% (95.0% CI: 14.0-21.0) experienced physical violence. There was no significant difference for sample size, professional group, quality score, or response rate. The frequency of physical and verbal violence in the subgroup analysis was statistically significantly different for countries and years. Conclusion Findings from this study provide useful information for policymaking regarding interventions to prevent or minimize violence against healthcare workers in the Eastern Mediterranean Region and Türkiye.