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Background and Aim: The curve of Spee (COS) is a physiological entity in human dentition. A functional masticatory system necessitates an appropriate occlusal curvature. The primary objective of this investigation was to assess the skeletal and dental parameters in individuals with variation in the depth of curve of Spee. Materials and Methods: A total of 276 patients with pre-treatment lateral cephalograms and dental cast models were investigated in the Orthodontics and Dentofacial Orthopedics Unit of a Tertiary Care Hospital of Mardan, Pakistan from January 2021 to December 2022. Patients with no prior history of orthopedic treatment for functional jaw, prosthodontic treatment, no prior history of cleft lip and palate and cranio-facial disorders were enrolled. Ethical approval was obtained and all the patients were categorized into three groups based on the depth of curve of Spee (COS): Group-I (flat curvature < 2 mm), Group-II (normal curvature 2-3 mm), and Group-III (deep curvature > 3 mm). Lateral cephalometric analysiswas done to measure the four angular and four linear parameters. Molar relation, overbite, COS depth, and overjet were measured based on the occlusal classification. SPSS version 27 was used for data analysis.

Explainable recommender systems (RS) have traditionally followed a one-size-fits-all approach, delivering the same explanation level of detail to each user, without considering their individual needs and goals. Further, explanations in RS have so far been presented mostly in a static and non-interactive manner. To fill these research gaps, we aim in this paper to adopt a user-centered, interactive explanation model that provides explanations with different levels of detail and empowers users to interact with, control, and personalize the explanations based on their needs and preferences. We followed a user-centered approach to design interactive explanations with three levels of detail (basic, intermediate, and advanced) and implemented them in the transparent Recommendation and Interest Modeling Application (RIMA). We conducted a qualitative user study (N=14) to investigate the impact of providing interactive explanations with varying level of details on the users' perception of the explainable RS. Our study showed qualitative evidence that fostering interaction and giving users control in deciding which explanation they would like to see can meet the demands of users with different needs, preferences, and goals, and consequently can have positive effects on different crucial aspects in explainable recommendation, including transparency, trust, satisfaction, and user experience., 23 pages

Significant attention has been paid to enhancing recommender systems (RS) with explanation facilities to help users make informed decisions and increase trust in and satisfaction with the RS. Justification and transparency represent two crucial goals in explainable recommendation. Different from transparency, which faithfully exposes the reasoning behind the recommendation mechanism, justification conveys a conceptual model that may differ from that of the underlying algorithm. An explanation is an answer to a question. In explainable recommendation, a user would want to ask questions (referred to as intelligibility types) to understand results given by the RS. In this paper, we identify relationships between Why and How explanation intelligibility types and the explanation goals of justification and transparency. We followed the Human-Centered Design (HCD) approach and leveraged the What-Why-How visualization framework to systematically design and implement Why and How visual explanations in the transparent Recommendation and Interest Modeling Application (RIMA). Furthermore, we conducted a qualitative user study (N=12) to investigate the potential effects of providing Why and How explanations together in an explainable RS on the users' perceptions regarding transparency, trust, and satisfaction. Our study showed qualitative evidence confirming that the choice of the explanation intelligibility types depends on the explanation goal and user type., 23 pages

The HRAS gene plays a crucial role in regulating essential cellular processes for life, and this gene's misregulation is linked to the development of various types of cancers. Nonsynonymous single nucleotide polymorphisms (nsSNPs) within the coding region of HRAS can cause detrimental mutations that disrupt wild-type protein function. In the current investigation, we have employed in-silico methodologies to anticipate the consequences of infrequent genetic variations on the functional properties of the HRAS protein. We have discovered a total of 50 nsSNPs, of which 23 were located in the exon region of the HRAS gene and denoting that they were expected to cause harm or be deleterious. Out of these 23, 10 nsSNPs ([G60V], [G60D], [R123P], [D38H], [I46T], [G115R], [R123G], [P11OL], [A59L], and [G13R]) were identified as having the most delterious effect based on results of SIFT analysis and PolyPhen2 scores ranging from 0.53 to 69. The DDG values −3.21 kcal/mol to 0.87 kcal/mol represent the free energy change associated with protein stability upon mutation. Interestingly, we identified that the three mutations (Y4C, T58I, and Y12E) were found to improve the structural stability of the protein. We performed molecular dynamics (MD) simulations to investigate the structural and dynamic effects of HRAS mutations. Our results showed that the stable model of HRAS had a significantly lower energy value of −18756 kj/mol compared to the initial model of −108915 kj/mol. The RMSD value for the wild-type complex was 4.40 Å, and the binding energies for the G60V, G60D, and D38H mutants were −107.09 kcal/mol, −109.42 kcal/mol, and −107.18 kcal/mol, respectively as compared to wild-type HRAS protein had −105.85 kcal/mol. The result of our investigation presents convincing corroboration for the potential functional significance of nsSNPs in augmenting HRAS expression and adding to the activation of malignant oncogenic signalling pathways.

Research on Human-Centered Learning Analytics (HCLA) has provided demonstrations of a successful co-design process for LA tools with different stakeholders. However, there is a need for 'quick and dirty' methods to allow the low-cost design of LA indicators. Recently, Indicator Specification Cards (ISC) have been proposed to help different learning analytics stakeholders co-design indicators in a systematic manner. In this paper, we aim at improving the user experience, flexibility, and reliability of the ISC-based indicator design process. To this end, we present the development details of an intuitive and theoretically-sound ISC user interface that allows the low-cost design of LA indicators. Further, we propose two approaches to support the flexible design of indicators, namely a task-driven approach and a data-driven approach., In Proceedings of 4th International Workshop on Human-Centred Learning Analytics (HCLA) co-located with the 13th International Learning Analytics and Knowledge Conference (LAK2023), Virtual, March 13, 2023

This article contributes to the limited empirical literature on the impact of decentralization on psychological wellbeing by investigating the hypothesis which signifies that shifts toward more fiscal decentralization in health services would be accompanied by improvements in health outcomes. Formulating a conventional public finance model applied to health care, this hypothesis is tested on a panel data of the Pakistan's provinces during the period 1990 to 2015. The empirical underpinning of the article suggested that the economic reforms of 2001 in Pakistan's healthcare sector, through fiscal decentralization, have imposed a substantial and positive influence on the effectiveness of the public policy in improving the healthcare outcomes over the examined period.

Evidences related to neuropsychological impact of COVID-19 and its long-term side effects are beginning to emerge that may take years to catalogue the number of diseases and their treatments. Nonetheless, as neuropsychologists are evaluating COVID-19 survivors, a debate related to the psychiatric and neurocognitive sequels of past outbreaks, along with the recurrent co- occurrence of PTSD and acquired brain injuries, may be enlightening. This paper is highlighting the emergence of mental health issues that can be addressed and treatments can be provided according to the need of time. Technology has also been increasing day by day according to the current needs of public. COVID- 19 crisis has now shifted the focus towards the role of digital health care. For ensuring the best and right use of tele-health and app tools in such crises, it is suggested that there is a need for training of mental health professionals to ensure proper protocols for improved efficacy.

Despite the acknowledgment that the perception of explanations may vary considerably between end-users, explainable recommender systems (RS) have traditionally followed a one-size-fits-all model, whereby the same explanation level of detail is provided to each user, without taking into consideration individual user's context, i.e., goals and personal characteristics. To fill this research gap, we aim in this paper at a shift from a one-size-fits-all to a personalized approach to explainable recommendation by giving users agency in deciding which explanation they would like to see. We developed a transparent Recommendation and Interest Modeling Application (RIMA) that provides on-demand personalized explanations of the recommendations, with three levels of detail (basic, intermediate, advanced) to meet the demands of different types of end-users. We conducted a within-subject study (N=31) to investigate the relationship between user's personal characteristics and the explanation level of detail, and the effects of these two variables on the perception of the explainable RS with regard to different explanation goals. Our results show that the perception of explainable RS with different levels of detail is affected to different degrees by the explanation goal and user type. Consequently, we suggested some theoretical and design guidelines to support the systematic design of explanatory interfaces in RS tailored to the user's context., Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (UMAP'22)

We investigate the role of a time and spin-dependent phase shift on the evolution of one-dimensional discrete-time quantum walks. By employing Floquet engineering, a time and spin-dependent phase shift ($\phi$) is imprinted onto the walker's wave function while it shifts from one lattice site to another. For a quantum walk driven by the standard protocol we show with our numerical simulations that complete revivals with equal periods occur in the probability distribution of the walk for rational values of the phase factor, i.e., $\phi/2\pi = p/q$. For an irrational value of $\phi/2\pi$ our results show partial revivals in the probability distribution with unpredictable periods, and the walker remains localized in a small region of the lattice. We further investigate revivals in a split-step quantum walk with a time and spin-dependent phase shift for rational values of $\phi/2\pi$. In contrast to the case of standard protocol, the split-step quantum walk shows partial revivals in the probability distribution. Furthermore, in view of an experimental realization we investigate the robustness of revivals against noise in the phase shift. Our results show that signatures of revivals persist for smaller values of the noise parameter, while revivals vanish for larger values. Our work is important in the context of quantum computation where quantum walks with a time and spin-dependent phase shift can be used to control and manipulate a desired quantum state on demand., Comment: 10 pages, 4 figures

Objective: This research study aimed to find out the association between physical activity and urinary incontinence in elderly population. Methods: A cross-sectional correlation study design was conducted with n=161 elderly male and female subjects with age ≥ 55 years. Non- probability convenience sampling was used in order to collect data from the respondents. Rapid Assessment of Physical Activity (RAPA) and MESA questionnaire was used to evaluate level of physical activity and presence of urinary incontinence. The association between physical activity and urinary incontinence was measured through Chi-square test. SPSS 21 was used to analyze the data. Results: The mean±SD age of subjects was 64.03± 9.56 years. Level of physical activity found to be significantly associated with urinary incontinence (p≤0.05). A significant association can be seen in participants who are sedentary (p=0.02), who perform moderate physical activity for 30 minutes/day for 5 days/week (p=0.04) and who perform strength activities (p

The objective of this thesis is to investigate the status of the crime of ‘terror’ as a war crime under international humanitarian law. Included in Article 51 (2) of Additional Protocol I and in Article 13 (2) of Additional Protocol II to the Geneva Conventions of 1949, the crime prohibits the ‘acts or threats of violence the primary purpose of which is to spread terror among the civilian population’. The thesis is structured in two parts. The first traces the historical development of the prohibition on spreading terror among the civilian population. It surveys the evolution of state practice and scrutinises the drafting history of the Additional Protocols. The second part focuses on the prosecution of the crime before international courts and tribunals. The jurisprudence of the International Criminal Tribunal for the Former Yugoslavia is given particular attention as the first international tribunal to prosecute the offence as a violation of laws and customs of war. Despite the case-law of the ad hoc Tribunals confirming the crime of ‘terror’ as an international crime in customary law, it was not included in the Rome Statute of International Criminal Court. The thesis explores the reasons for this and advances an argument for extending the subject-matter jurisdiction of the International Criminal Court to include the crime of ‘terror’. In doing so, the thesis examines the conflation of ‘terror’ as a war crime with the offence of ‘terrorism’ in order to add clarity to the conceptualization of the former under international humanitarian law.

Yeast extract is widely used in different food industries as a flavoring agent or vitamin supplement. In this study, a process was optimized for the production of yeast extract from Baker’s yeast (Saccharomyces cerevisiae). A glass vessel stirred fermenter was used for the cultivation of yeast biomass. The effect of various physical and chemical factors was evaluated on the production of yeast cells and optimum conditions for the production of maximum yeast biomass were determined. The optimum growth was obtained at 30ºC with pH 4.5 using molasses as a substrate supplemented with urea at 150rpm. Yeast cells were then separated by centrifugation and ruptured and autolysis was observed to be the most feasible method. Among various method employed to dry the yeast extract, spray dryer appeared as most efficient one. Yeast extract obtained after drying was subjected to different analyses and compared with commercial yeast extract. The produced yeast extract was applied in media preparation to grow different microorganisms including yeast, bacteria and fungi and considerable growth was observed. These results indicated that the developed process is a cost effective alternate approach for the production of yeast extract.

Diabetes Mellitus is commonly known as diabetes. It is one of the most chronic diseases as the World Health Organization (WHO) report shows that the number of diabetes patients has risen from 108 million to 422 million in 2014. Early diagnosis of diabetes is important because it can cause different diseases that include kidney failure, stroke, blindness, heart attacks, and lower limb amputation. Different diabetes diagnosis models are found in the literature, but there is still a need to perform a survey to analyze which model is best. This paper performs a literature review for diabetes diagnosis approaches using Artificial Intelligence (neural networks, machine learning, deep learning, hybrid methods, and/or stacked-integrated use of different machine learning algorithms). More than thirty-five papers have been shortlisted that focus on diabetes diagnosis approaches. Different datasets are available online for the diagnosis of diabetes. Pima Indian Diabetes Dataset (PIDD) is the most commonly used for diabetes prediction. In contrast with other datasets, it has key factors which play an important role in diabetes diagnosis. This survey also throws light on the weaknesses of the existing approaches that make them less appropriate for a diabetes diagnosis. In artificial intelligence techniques, deep learning is widespread and in medical research, heart rate is getting more attention. Deep learning combined with other algorithms can give better results in diabetes diagnosis and heart rate should be used for other cardiac disease diagnoses.

Background Medical students face greater academic stress and devote more time to their studies due to the tough nature of medical education, at the cost of sleep and physical activity. Good sleep quality and physical activity improve the mental ability and academic performance of the students. Objectives and rationale The study aims to assess sleep quality and physical activity levels among fourth-year MBBS students of Rawalpindi Medical University. We compare these levels with gender and boarding status and correlate them with the academic performance of the students. This may provide new target areas to improve the academics of students performing below average. Materials and methods It was a descriptive, cross-sectional study conducted in March 2019 on 344 medical students enrolled in the fourth-year MBBS class of Rawalpindi Medical University. Sleep quality was assessed by the Pittsburgh Sleep Quality Index (PSQI), physical activity levels by the Global Physical Activity Questionnaire (GPAQ), and academic performance by the marks attained in the most recent pathology class test. The students who could not prepare for the test in the usual manner were excluded from the study. Two-hundred nineteen (219) students were part of the final study sample. Data analysis was performed using SPSS v.22.0 (IBM Corp, Armonk, NY, US). A chi-squared test, independent samples t-test, Pearson’s correlation, and a multiple linear regression model were used to assess the variables. Results Sleep quality and physical activity were significantly correlated with academic performance (p-values of the chi-square and t-test were

Objective Worldwide work place violence is a very serious issue. Compared with other occupational groups health care workers (HCW) are at a higher risk of violence or aggression. The objective of this study was to identify the prevalence of violence and the demographic factors among HCWs.Materials and Methods: This cross sectional study was conducted at District Head Quarter Hospital, Sheikhupura. Willing doctors and nurses were included in this survey. An English self-designed questionnaire was used for data collection. The quantitative variables like age were presented mean ± SD. Qualitative variables like gender and other demographic variables were presented as frequency and percentages. For qualitative portion, themes were identifies according to the response using NVIVO.Results: Total number of participants included were 199 into this study. Mean age was found as 30.69 ± 8.02 years. Maximum of participants (61.3%) were female. Most common type was verbal aggression (75.8%). Most common place of violence was emergency room (86.2%) & morning time (50.9%). Male doctors frequently observed violence behavior than female, however difference was not significant. Also violence was significantly more commonly observed in surgery & medicine department also well as in youngster with less experience (P ˂ 0.05).Conclusion: This study concluded that young health care workers face more violence. Behavior of this society may discourage the moral of young HCWs. Policies & education to prevent these events is need of time., Amaç: Dünya çapında işyeri şiddeti çok ciddi bir konudur. Diğer meslek gruplarıyla karşılaştırıldığında sağlık çalışanlarına yönelik şiddet veya saldırganlık riski daha yüksektir. Bu çalışmanın amacı, sağlık çalışanlarının şiddet prevalansını ve demografik faktörleri tespit etmektir.Materyal ve Metot: Bu kesitsel çalışma Sheikhupura İlçesi Merkez Mahallesi Hastanesi'nde yapıldı. Gönüllü doktor ve hemşireler bu ankete dahil edildi. Veri toplama için İngilizce olarak tasarlanan bir anket kullanılmıştır. Yaş gibi nicel değişkenler ortalama ± SD olarak sunuldu. Cinsiyet ve diğer demografik değişkenler gibi nitel değişkenler sıklık ve yüzde olarak sunuldu. Niteliksel kısım için temalar, NVIVO kullanılarak verilen cevaplara göre tanımlandı.Bulgular: Bu çalışmaya katılan toplam katılımcı sayısı 199 idi. Ortalama yaş 30,69 ± 8,02 yıl olarak bulundu. En fazla katılımcı (% 61,3) kadındı. En sık görülen tip sözel saldırganlık (% 75,8) idi. En sık görülen şiddet yeri acil servisteydi (% 86,2) ve sabah vakti (% 50,9) idi. Erkek doktorlar sık ​​sık kadınlara göre şiddet davranışları gözlemlemişler, fakat istatistiksel fark anlamlı bulunamamıştır. Şiddet, cerrahi ve tıp bölümünde de daha az deneyime sahip gençlerde olduğu gibi, daha da yaygın olarak gözlendi (P ˂ 0,05).Sonuç: Bu çalışmada genç sağlık çalışanlarının daha fazla şiddete maruz kaldığı sonucuna varılmıştır. Toplumun bu davranışı, genç sağlık çalışanlarının ahlakını zedeleyebilir. Bu olayları önlemek için eğitim ve politikalara zaman ihtiyaç duyar.

International audience; The high resolution integration of bread wheat genetic and genomic resources accumulated during the last decades offers the opportunity to unveil candidate genes driving major agronomical traits to an unprecedented scale. We combined 27 public quantitative genetic studies and four genetic maps to deliver an exhaustive consensus map consisting of 140,315 molecular markers hosting 221, 73, and 82 Quantitative Trait Loci (QTL) for respectively yield, baking quality, and grain protein content (GPC) related traits. Projection of the consensus genetic map and associated QTLs onto the wheat syntenome made of 99,386 genes ordered on the 21 chromosomes delivered a complete and non-redundant repertoire of 18, 8, 6 metaQTLs for respectively yield, baking quality and GPC, altogether associated to 15,772 genes (delivering 28,630 SNP-based makers) including 37 major candidates. Overall, this study illustrates a translational research approach in transferring information gained from grass relatives to dissect the genomic regions hosting major loci governing key agronomical traits in bread wheat, their flanking markers and associated candidate genes to be now considered as a key resource for breeding programs.

The high resolution integration of bread wheat genetic and genomic resources accumulated during the last decades offers the opportunity to unveil candidate genes driving major agronomical traits to an unprecedented scale. We combined 27 public quantitative genetic studies and four genetic maps to deliver an exhaustive consensus map consisting of 140,315 molecular markers hosting 221, 73, and 82 Quantitative Trait Loci (QTL) for respectively yield, baking quality, and grain protein content (GPC) related traits. Projection of the consensus genetic map and associated QTLs onto the wheat syntenome made of 99,386 genes ordered on the 21 chromosomes delivered a complete and non-redundant repertoire of 18, 8, 6 metaQTLs for respectively yield, baking quality and GPC, altogether associated to 15,772 genes (delivering 28,630 SNP-based makers) including 37 major candidates. Overall, this study illustrates a translational research approach in transferring information gained from grass relatives to dissect the genomic regions hosting major loci governing key agronomical traits in bread wheat, their flanking markers and associated candidate genes to be now considered as a key resource for breeding programs.

Background: Diabetes mellitus is a chronic metabolic disorder of hyperglycemia. Chronic hyperglycemia produces advanced glycation end products such as the methylglyoxal (MGO) which interferes with cell functions, insulin signaling, and β-cell functions. The present study was conducted to determine the effects of berberine (BBR) therapy on serum MGO and insulin resistance in newly diagnosed type 2 diabetic patients. Materials and Methods: The present case–control study was conducted at the Department of Medicine, Liaquat University of Medical and Health Sciences, Jamshoro/Hyderabad, from March 2016 to January 2017. A sample of 200 newly diagnosed type 2 diabetic patients was divided into two groups. Group 1 received metformin 500 mg (×3 daily) and Group 2 received BBR 500 mg (×3 daily) for 3 months. Blood samples were collected at baseline and after 3 months to analyze biochemical parameters on Roche biochemical analyzer. MGO was assayed by ELISA kit and homeostasis model assessment of insulin resistance (HOMA-IR) model. SPSS version 23.0 (IBM, Incorporation, USA) analyzed the data at 95% confidence interval (P ≤ 0.05). Results: Baseline HOMA-IR (% IR) and MGO were found elevated in metformin and BBR groups. After 3 months of metformin and BBR therapy, the HOMA-IR (% IR) and MGO were decreased to 3.69 ± 1.13 and 2.64 ± 0.76 and 35.84 ± 12.56 and 26.64 ± 10.73 ng/dl, respectively (P = 0.0001). HOMA-IR (% IR) was improved by 40% and 73% (P = 0.0001) and MGO by 43% and 56% in metformin and BBR groups, respectively (P = 0.0001). Conclusion: BBR is more effective in decreasing the serum MGO levels and insulin resistance through improved glycemic control in newly diagnosed type 2 diabetic patients.

The present study was conducted to check the trend analysis of area and production for Sorghum in Pakistan. The findings of the study are based on sorghum area and production by using the data from 1990 to 2011. Four Models of trend analysis were applied but most appropriate Model for trend analysis of the present study was Quadratic Trend Model. Forecasting was also done up to 2017 for checking the future outlook. Forecast values are very close to actual values and have positive decreasing trend in Pakistan.

The present study was conducted to check the trend analysis of area and production for Sorghum in Pakistan. The findings of the study are based on sorghum area and production by using the data from 1990 to 2011. Four Models of trend analysis were applied but most appropriate Model for trend analysis of the present study was Quadratic Trend Model. Forecasting was also done up to 2017 for checking the future outlook. Forecast values are very close to actual values and have positive decreasing trend in Pakistan.