A cephalometric assessment of the nasolabial angle of an adult Nigerian population

Objective: One of the most important components of orthodontic diagnosis and treatment planning is an evaluation of the patient\u27s soft tissue profile. An assessment of the nasolabial angle is a vital component of this evaluation. The purpose of this study was to establish norms for the nasolabial angle of an adult Nigerian population; compare the male and female values and to compare the values obtained for Nigerians with those reported for other populations. Method: Lateral cephalometric radiographs of one hundred students (44 males and 56 females) of the College of Medicine, University of Lagos, aged 18-25years were taken. Selected subjects were of Nigerian ancestry with normal occlusion. The radiographs were manual ly t raced and the nasolabial angle of each subject measured. Result: A mean value of 84.35° +13.71° was computed for the entire sample. No statistically significant difference was observed between the male and female values (p>0.05), although 0 0 the males recorded a lower nasolabial angle (83.70 ) than the females (85.28 ).The nasolabial angle recorded in this study was similar to that reported for South African blacks, but much lower than that reported for Caucasian populations.Conclusion: The mean nasolabial angle of 84.35 + 13.71 was observed in the Nigerian population studied. Sexual differences were not observed; however, the values observed in this study differ from that reported for Caucasians and other racial groups

Interspecific comparisons of C\u3csub\u3e3\u3c/sub\u3e turfgrass for tennis use: II. Investigaion of ball friction, ball bounce, and associated factors in replicated grass courts

Tennis is played on many different surfaces including natural grass, which plays fast because of low ball bounce (i.e., coefficient of restitution [COR]) and low ball‐to‐surface friction (coefficient of friction [COF]) that increase the pace (ball speed) of tennis. Effects of various C3 turfgrasses on COF and COR have not been investigated. Our objectives were to evaluate eight cultivars of various species randomized within three official size tennis courts: (a) ‘Keeneland’ Kentucky bluegrass (Poa pratensis L., KB), (b) ‘Rubix’ KB, (c) ‘Villa’ velvet bentgrass (Agrostis canina L., VBG), (d) ‘Puritan’ colonial bentgrass (Agrostis capillaris L., CL), (e) ‘007’ creeping bentgrass (Agrostis stolonifera L., CB), (f) fine fescue (Festuca sp., FF) mixture, (g) ‘Karma’ perennial ryegrass (Lolium perenne L, PR), and (h) ‘Wicked’ PR. Friction was measured using a weighted sled and ball bounce (BB) to derive COR was measured using a vertical drop height of 254 cm. Bounce (i.e., COR) to satisfy the International Tennis Federation (ITF) minimum of 50% BB (COR = 0.70) was not observed on any of the species evaluated. Species such as FF and PR were able to achieve BB to satisfy the ITF 80% BB minimum to that observed on smooth concrete. Linear regression indicated that 170g of surface hardness for FF and PR to as much as 200g on KB and higher on BG may be needed to achieve a COR = 0.70. Hemi‐ and lignocellulose cell wall fractions were correlated with COR and COF but exhibited significant and opposite relationships. Achieving higher COF may be a more practical means to slow court pace of notoriously fast grass courts. Future research will be needed to investigate the effects of cultural practices on COF

Typologie des exploitations agropastorales du terroir de la NEMA (Sénégal, West Africa)

Dans le terroir de la Néma, pour améliorer les rendements dans un contexte de baisse drastique des superficies cultivables et de la fertilité des sols, les agro-pasteurs ont recours à une gestion intégrée des productions agricoles et animales. Ainsi, suivant leur structure, les exploitations agricoles présentent des formes d’organisation diverses. Pour appréhender cette diversité, deux approches ont été utilisées: l’approche socio-économique (enquête) pour définir les caractéristiques des exploitations et l’approche agronomique visant à évaluer les ressources agricoles. Le traitement des données a permis de distinguer suivant la production et l’utilisation des résidus de récolte, deux groupes d’exploitations : celles qui produisent et utilisent, outre les autres résidus, les résidus de sorgho (A) et celles qui ne produisent et n’utilisent pas ces derniers (B); et suivant la taille, trois groupes d’exploitations: celles de grande taille (B1), de taille moyenne (A et B2) et de petite taille (B3). Si la production et l’épandage du fumier sont généralisés dans les groupes d’exploitations A, B1 et B2, ils sont peu développés dans les petites exploitations (B3). Et ce, du fait de l’absence ou de l’insuffisance du cheptel et de l’outillage agricole dans ces dernières, mais aussi de la faiblesse de la main d’oeuvre. La main d’oeuvre suivant les groupes d’exploitations est évaluée à 3,4 actifs agricoles dans le groupe B3 contre 6,4 ; 7,8 et 17 actifs agricoles respectivement pour les groupes d’exploitations B2, A et B1.Mots clés: Résidus de récolte, gestion intégrée, fertilité, fumier, unités agricole

A Predictive Model for User Motivation and Utility Implications of Privacy-Protection Mechanisms in Location Check-Ins

Location check-ins contain both geographical and semantic information about the visited venues. Semantic information is usually represented by means of tags (e.g., “restaurant”). Such data can reveal some personal information about users beyond what they actually expect to disclose, hence their privacy is threatened. To mitigate such threats, several privacy protection techniques based on location generalization have been proposed. Although the privacy implications of such techniques have been extensively studied, the utility implications are mostly unknown. In this paper, we propose a predictive model for quantifying the effect of a privacy-preserving technique (i.e., generalization) on the perceived utility of check-ins. We first study the users’ motivations behind their location check-ins, based on a study targeted at Foursquare users (N = 77). We propose a machine-learning method for determining the motivation behind each check-in, and we design a motivation-based predictive model for the utility implications of generalization. Based on the survey data, our results show that the model accurately predicts the fine-grained motivation behind a check-in in 43% of the cases and in 63% of the cases for the coarse-grained motivation. It also predicts, with a mean error of 0.52 (on a scale from 1 to 5), the loss of utility caused by semantic and geographical generalization. This model makes it possible to design of utility-aware, privacy-enhancing mechanisms in location-based online social networks. It also enables service providers to implement location-sharing mechanisms that preserve both the utility and privacy for their users

ORide: A Privacy-Preserving yet Accountable Ride-Hailing Service

In recent years, ride-hailing services (RHSs) have be- come increasingly popular, serving millions of users per day. Such systems, however, raise significant privacy concerns, because service providers are able to track the precise mobility patterns of all riders and drivers. In this paper, we propose ORide (Oblivious Ride), a privacy- preserving RHS based on somewhat-homomorphic en- cryption with optimizations such as ciphertext packing and transformed processing. With ORide, a service provider can match riders and drivers without learning their identities or location information. ORide offers rid- ers with fairly large anonymity sets (e.g., several thou- sands), even in sparsely populated areas. In addition, ORide supports key RHS features such as easy payment, reputation scores, accountability, and retrieval of lost items. Using real data-sets that consist of millions of rides, we show that the computational and network over- head introduced by ORide is acceptable. For example, ORide adds only several milliseconds to ride-hailing op- erations, and the extra driving distance for a driver is less than 0.5 km in more than 75% of the cases evaluated. In short, we show that a RHS can offer strong privacy guar- antees to both riders and drivers while maintaining the convenience of its services

SmarPer: Context-Aware and Automatic Runtime-Permissions for Mobile Devices

Permission systems are the main defense that mobile platforms, such as Android and iOS, offer to users to protect their private data from prying apps. However, due to the tension between usability and control, such systems have several limitations that often force users to overshare sensitive data. In this work, we address some of these limitations with SmarPer, an advanced permission mechanism for Android. First, to address the rigidity of current permission systems and their poor matching of users' privacy preferences, SmarPer relies on contextual information and machine learning to predict permission decisions at runtime. Using our SmarPer implementation, we collected 8,521 runtime permission decisions from 41 participants in real conditions. Note that the goal of SmarPer is to mimic the users decisions, not to make privacy-preserving decisions per se. With this unique data set, we show that tting an efcient Bayesian linear regression model results in a mean correct classication rate of 80% (3%). This represents a mean relative improvement of 50% over a user-dened static permission policy, i.e., the model used in current permission systems. Second, SmarPer also focuses on the suboptimal trade-off between privacy and utility; instead of only “allow” or “deny” decisions, SmarPer also offers an “obfuscate” option where users can still obtain utility by revealing partial information to apps. We implemented obfuscation techniques in SmarPer for different data types and evaluated them during our data collection campaign. Our results show that 73% of the participants found obfuscation useful and it accounted for almost a third of the total number of decisions. In short, we are the first to show, using a large dataset of real in situ permission decisions, that it is possible to learn users’ unique decision patterns at runtime using contextual information while supporting data obfuscation; this an important step towards automating the management of permissions in smartphones

Polymers in Curved Boxes

We apply results derived in other contexts for the spectrum of the Laplace operator in curved geometries to the study of an ideal polymer chain confined to a spherical annulus in arbitrary space dimension D and conclude that the free energy compared to its value for an uncurved box of the same thickness and volume, is lower when $D < 3$, stays the same when $D = 3$, and is higher when \mbox{$D > 3$}. Thus confining an ideal polymer chain to a cylindrical shell, lowers the effective bending elasticity of the walls, and might induce spontaneous symmetry breaking, i.e. bending. (Actually, the above mentioned results show that {\em {any}} shell in $D = 3$ induces this effect, except for a spherical shell). We compute the contribution of this effect to the bending rigidities in the Helfrich free energy expression.Comment: 20 pages RevTeX, epsf; 4 figures; submitted to Macromoledule

PERBANDINGAN KANDUNGAN MINYAK ATSIRI TANAMAN SEREH WANGI (Cymbopogon nardus L. Rendle) YANG DITANAM DI LOKASI BERBEDA

It has been conducted a research that aims to determine the ratio of essential oil content of citronella stalks (Cymbopogon nardus Rendle L.) grown in the lowlands of Denpasar and the highlands of Bedugul. The experiment was conducted by using experimental designs. The parameters measured were the volume and the level of citronella oil produced. The sample preparation of powdered citronella stalks was as much as 200 grams, macerated with 96% ethanol and evaporated with Vacuum rotary evaporator to form condensed extract. The research used quantitative methods. The volume of hydro distillation was to obtain a crude extract of citronella stalks and the identification of active compounds was conducted by using Gas Chromatography / Mass Spectrometry (GC-MS). It can be concluded that the levels of citronella essential oil stalks from the highland of Bedugul was higher than the lowland areas of Denpasar, while the quality of essential oil of the lowland of Denpasar was better than that of the Bedugul highland. The content of secondary metabolites of the results of GC-MS analysis obtained from the essential oils contained in the analyzed crude extract of citronella stalks namely the compound of Selina-6-en-4-ol (2287322), the compound of n-hexadecanoic acid (1238019) and the compound of Driman-8,11-diol from the lowland of Denpasar while the Selina compound-6-en-4-ol (1856137) from the highland of Bedugul. Keywords: Citronella, essential oil content, altitud

PrivateRide: A Privacy-Enhanced Ride-Hailing Service

In the past few years, we have witnessed a rise in the popularity of ride-hailing services (RHSs), an on-line marketplace that enables accredited drivers to use their own cars to drive ride-hailing users. Unlike other transportation services, RHSs raise significant privacy concerns, as providers are able to track the precise mobility patterns of millions of riders worldwide. We present the first survey and analysis of the privacy threats in RHSs. Our analysis exposes high-risk privacy threats that do not occur in conventional taxi services. Therefore, we pro- pose PrivateRide, a privacy-enhancing and practical solu- tion that offers anonymity and location privacy for riders, and protects drivers’ information from harvesting attacks. PrivateRide lowers the high-risk privacy threats in RHSs to a level that is at least as low as that of many taxi services. Using real data-sets from Uber and taxi rides, we show that PrivateRide significantly enhances riders’ privacy, while preserving tangible accuracy in ride matching and fare calculation, with only negligible effects on convenience. Moreover, by using our Android implementation for experimental evaluations, we show that PrivateRide’s overhead during ride setup is negligible. In short, we enable privacy- conscious riders to achieve levels of privacy that are not possible in current RHSs and even in some conventional taxi services, thereby offering a potential business differentiator

Consensual and Privacy-Preserving Sharing of Multi-Subject and Interdependent Data

Individuals share increasing amounts of personal data online. This data often involves–or at least has privacy implications for–data subjects other than the individuals who shares it (e.g., photos, genomic data) and the data is shared without their consent. A sadly popular example, with dramatic consequences, is revenge pornography. In this paper, we propose ConsenShare, a system for sharing, in a consensual (wrt the data subjects) and privacy-preserving (wrt both service providers and other individuals) way, data involving subjects other than the uploader. We describe a complete design and implementation of ConsenShare for photos, which relies on image processing and cryptographic techniques, as well as on a two-tier architecture (one entity for detecting the data subjects and contacting them; one entity for hosting the data and for collecting consent). We benchmark the performance (CPU and bandwidth) of ConsenShare by using a dataset of 20k photos from Flickr. We also conduct a survey targeted at Facebook users (N = 321). Our results are quite encouraging: The experimental results demonstrate the feasibility of our approach (i.e., acceptable overheads) and the survey results demonstrate a potential interest from the users